1284 Vertex Jobs - Page 12

Your role Develop and implement Generative AI / AI solutions on Google Cloud Platform Work with cross-functional teams to design and deliver AI-powered products and services Work on developing, versioning and executing Python code Deploy models as endpoints in Dev Environment Solid understanding of python Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX Experience with natural language processing (NLP) and machine learning (ML) Experience on Cloud storage, compute engine, VertexAI, Cloud Function, Pub/Sub, Vertex AI etc Hands on experience with Generative AI support in Vertex, specifically handson experience with Generative AI models like Gemini, vertex Search etc Your Profile Relevant 4-6+ years of experience in AI development Experience with Google Cloud Platform specifically delivering an AI solution on VertexAI platform Experience in developing and deploying AI Solutions What youll love about working here You can shape your with us. We offer a range of career paths and internal opportunities within Capgemini group. You will also get personalized career guidance from our leaders. You will get comprehensive wellness benefits including health checks, telemedicine, insurance with top-ups, elder care, partner coverage or new parent support via flexible work. You will have the on one of the industry's largest digital learning platforms, with access to 250,000+ courses and numerous certifications. Were committed to ensure that people of all backgrounds feel encouraged and have a sense of belonging at Capgemini. You are valued for who you are, and you can. Every Monday, kick off the week with a musical performance by our in-house band - The Rubber Band. Also get to participate in internal, yoga challenges, or marathons. At Capgemini, you can work on in tech and engineering with industry leaders or create to overcome societal and environmental challenges. About Capgemini Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. Location - Mumbai,Bengaluru,Chennai,Pune,Hyderabad

We are seeking a visionary AI Architect to lead the design and integration of cutting-edge AI systems, including Generative AI , Large Language Models (LLMs) , multi-agent orchestration , and retrieval-augmented generation (RAG) frameworks. This role demands a strong technical foundation in machine learning, deep learning, and AI infrastructure, along with hands-on experience in building scalable, production-grade AI systems on the cloud. The ideal candidate combines architectural leadership with hands-on proficiency in modern AI frameworks, and can translate complex business goals into innovative, AI-driven technical solutions. Primary Stack & Tools: Languages : Python, SQL, Bash ML/AI Frameworks : PyTorch, TensorFlow, Scikit-learn, Hugging Face Transformers GenAI & LLM Tooling : OpenAI APIs, LangChain, LlamaIndex, Cohere, Claude, Azure OpenAI Agentic & Multi-Agent Frameworks : LangGraph, CrewAI, Agno, AutoGen Search & Retrieval : FAISS, Pinecone, Weaviate, Elasticsearch Cloud Platforms : AWS, GCP, Azure (preferred: Vertex AI, SageMaker, Bedrock) MLOps & DevOps : MLflow, Kubeflow, Docker, Kubernetes, CI/CD pipelines, Terraform, FAST API Data Tools : Snowflake, BigQuery, Spark, Airflow Key Responsibilities: Architect scalable and secure AI systems leveraging LLMs , GenAI , and multi-agent frameworks to support diverse enterprise use cases (e.g., automation, personalization, intelligent search). Design and oversee implementation of retrieval-augmented generation (RAG) pipelines integrating vector databases, LLMs, and proprietary knowledge bases. Build robust agentic workflows using tools like LangGraph , CrewAI , or Agno , enabling autonomous task execution, planning, memory, and tool use. Collaborate with product, engineering, and data teams to translate business requirements into architectural blueprints and technical roadmaps. Define and enforce AI/ML infrastructure best practices , including security, scalability, observability, and model governance. Manage technical road-map, sprint cadence, and 3–5 AI engineers; coach on best practices. Lead AI solution design reviews and ensure alignment with compliance, ethics, and responsible AI standards. Evaluate emerging GenAI & agentic tools; run proofs-of-concept and guide build-vs-buy decisions. Qualifications: 10+ years of experience in AI/ML engineering or data science, with 3+ years in AI architecture or system design. Proven experience designing and deploying LLM-based solutions at scale, including fine-tuning , prompt engineering , and RAG-based systems . Strong understanding of agentic AI design principles , multi-agent orchestration , and tool-augmented LLMs . Proficiency with cloud-native ML/AI services and infrastructure design across AWS, GCP, or Azure. Deep expertise in model lifecycle management, MLOps, and deployment workflows (batch, real-time, streaming). Familiarity with data governance , AI ethics , and security considerations in production-grade systems. Excellent communication and leadership skills, with the ability to influence technical and business stakeholders.

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Google Cloud Platform Architecture Good to have skills : Google Cloud Machine Learning Services Minimum 3 Year(s) Of Experience Is Required Educational Qualification : 15 years full time education Summary: As an AI/ML technical lead, you will be responsible for developing applications and systems that utilize AI tools and Cloud AI services. Your typical day will involve applying CCAI and GenAI models as part of the solution, utilizing deep learning, neural networks and chatbots. Roles & Responsibilities: - Design and develop CCAI applications and systems utilizing Google Cloud Machine Learning Services, dialogue flow CX, agent assist. - Develop and implement chatbot solutions that integrate seamlessly with CCAI and other Cloud services - Integrate Dialogflow agents with various platforms, such as Google Assistant, Facebook Messenger, Slack, and websites. Hands-on experience with IVR integration and telephony systems such as Twilio, Genesys, Avaya - Integrate with IVR systems and Proficiency in webhook setup and API integration. - Develop Dialogflow CX - flows, pages, webhook as well as playbook and integration of tool into playbooks. - Creation of agents in Agent builder and integrating them into end end to pipeline using python. - Apply GenAI-Vertex AI models as part of the solution, utilizing deep learning, neural networks, chatbots, and image processing. - Work with Google Vertex AI for building, training and deploying custom AI models to enhance chatbot capabilities - Implement and integrate backend services (using Google Cloud Functions or other APIs) to fulfill user queries and actions. - Document technical designs, processes, and setup for various integrations. - Experience with programming languages such as Python/Node.js Professional & Technical Skills: - Must To Have Skills: CCAI/Dialogflow CX hands on experience and generative AI understanding. - Good To Have Skills: Cloud Data Architecture, Cloud ML/PCA/PDE Certification, - Strong understanding of AI/ML algorithms and techniques. - Experience with chatbot , generative AI models, prompt Engineering - Experience with cloud or on-prem application pipeline with production-ready quality. Additional Information: - The candidate should have a minimum of 5 years of experience in Google Cloud Machine Learning Services/Gen AI/Vertex AI/CCAI. - The ideal candidate will possess a strong educational background in computer science, mathematics, or a related field, along with a proven track record of delivering impactful data-driven solutions. - A 15-year full time education is required, 15 years full time education

Vice President/Delivery- Generative AI/ConversationalAI/Vertex AI/Google Dialogflow 17+ years of experience Hybrid role. Noida/Gurugram/Pune/Bangalore Generative AI/Agentic AI experience with vertex AI/CCaaS/Google dialogflowCX. conversational agents/Autonomous Agent/Voice Bot/DigitalCX/Vertex AI/Google CCAI. end to end delivery experience required for global projects. Strong python experience. great communications. client facing role.

Skill required: Digital Inside Sales - Inside Sales Designation: Delivery Lead Manager Qualifications: Any Graduation Years of Experience: 13 to 18 years About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song— all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com What would you do? This position is responsible for leading the drive of product adoption, deliver high levels of business value, and cultivate deep internal and external customer relationships. This role will assist with all aspects of renewals, account management, adoption, customer success planning, and expansion sales. The role drives overall customer satisfaction including reporting and analytics of revenue impact tied to client success, client testimonials, and client references. ESSENTIAL JOB FUNCTIONS AND RESPONSIBILITIES: Ensure that employees are connecting and aligning their work and goals to the Enterprise Objectives. Drive adoption of Winning Way behaviors. Support and drive attainment of core company metrics. Align with and ensure Customer Success Management team is aligned with goals of Chief Customer Officer and Customer Center of Excellence team. Work with Zone and Line of Business Owners to ensure alignment with operational strategy and goals. Transform and evolve the Customer Success Management Team to align with operational strategy and goals. Collaborate and align with Line of Business Owners, Product Managers and Product Owners on roadmap deliverables and messaging so that the Manager of CSM can train and educate the team on upcoming releases and roadmaps. Personally manage escalations from dire Provide support for lead/opportunity generation: conduct calls / send emails / connect via social media to generate leads, schedule first meetings for sales/pre-sales, conduct customer surveys, identify participants for events, and bring awareness of the product or offering on behalf of sales/marketing teams. What are we looking for? KNOWLEDGE, SKILLS AND ABILITIES: Continually seeks opportunities to increase customer satisfaction and deepen client relationships. Excellent technical aptitude with the ability to analyze and decipher large amounts of customer data. Excellent communication skills, including issue tracking, triaging and crisis management. Ability to efficiently manage multiple customer projects simultaneously. Ability to communicate with internal and external customers and all levels of management. KNOWLEDGE, SKILLS AND ABILITIES: Continually seeks opportunities to increase customer satisfaction and deepen client relationships. Excellent technical aptitude with the ability to analyze and decipher large amounts of customer data. Excellent communication skills, including issue tracking, triaging and crisis management. Ability to efficiently manage multiple customer projects simultaneously. Ability to communicate with internal and external customers and all levels of management. Roles and Responsibilities: Ensure that employees are connecting and aligning their work and goals to the Enterprise Objectives. Drive adoption of Winning Way behaviors. Support and drive attainment of core company metrics. Align with and ensure Customer Success Management team is aligned with goals of Chief Customer Officer and Customer Center of Excellence team. Work with Zone and Line of Business Owners to ensure alignment with operational strategy and goals. Transform and evolve the Customer Success Management Team to align with operational strategy and goals. Collaborate and align with Line of Business Owners, Product Managers and Product Owners on roadmap deliverables and messaging so that the Manager of CSM can train and educate the team on upcoming releases and roadmaps. Personally manage escalations from direct reports and follow a methodical escalation process to leadership Lead the development of the relationship of the CSM team as the trusted advisor relationship with customer stakeholders and executive sponsors to drive product adoption and ensure they are leveraging the solution to achieve full business value. Act as an extension of the customer, being a proactive advocate within Vertex and the customer to accomplish defined objectives. This includes working with the various internal Support teams. Proactively grow the breadth and depth of strategic relationships with customers. Identify opportunities for continuous improvement. Define and oversee lifecycle processes/touch points, including QBR process, "listening" points (e.g. on usage, NPS), and measuring business value, penetration, usage, and adoption. Partner with internal stakeholders (from executive to supervisor) to align account activities with the customer’s business case and strategy. Responsible to help identify data driven revenue expansion within the customer base throughout all customer lifecycles. Work with leadership to identify annual targets Responsible for change management. Closely managing and nurturing accounts to identify and eliminate risk of attrition through regular touch points (conference calls, client visits, webinars, etc.). Establishing trusted relationships with customers, sustaining relationships through the full life cycle of the subscription ensuring their success., Any Graduation

About Kapiva: Kapiva is a modern ayurvedic nutrition brand focused on bringing selectively sourced, natural foods to Indian consumers. We help bring the wisdom of India’s ancient food traditions to modern-day consumers. Kapiva's high-quality portfolio offers products across various therapy areas including skin & hair, digestion, weight management, immunity, chronic issues, & much more. Our products are top performers on online marketplaces (Amazon, Flipkart, Big Basket, Nykaa, etc), we're growing our presence offline in a big way (Reliance, Nature’s Basket, Noble Plus etc.) & are funded by India’s best Consumer VC Funds – Orbimed Fireside Ventures, Vertex Ventures, Sharrp Ventures, 3One4 Capital & Jetty Ventures. The team at Kapiva is headed by the Co-Founders: Ameve Sharma: worked @McKinsey, @Baidyanath studied @INSEAD & NYU https://www.linkedin.com/in/amevesharma/ Shantanu S: Ex-PG & CMO Uniqlo India ; IIM C Alum https://www.linkedin.com/in/shantanu-b535a010/ Anuj Sharma: Ex- Hotstar , Ex- Myntra ; ISB https://www.linkedin.com/in/anuj-sharma-28033a40/ We’re creating a new brand with a unique story & are looking for a team to help us grow our business. You’d be joining a young, hungry team with a culture of honesty, humility, & hard work. Role Overview The Head of App & Website will be responsible for overseeing the app and web platforms, ensuring seamless user experiences, managing personalization initiatives, driving app growth, and enhancing customer retention through merchandise and conversion optimization strategies. Key Responsibilities: App Growth and Feature Marketing: Product Marketing - Identify the key features to be developed on App based on consumer Insights and Company Objective - Develop and execute app growth strategies including user acquisition, activation, and retention. - Collaborate with the marketing team to promote new app features and service offerings to consumers. - Implement in-app marketing campaigns and work with CRM team for personalized push notifications. - Leverage data insights to recommend new features and enhancements to improve app stickiness and user engagement. - Monitor app store performance, optimize ASO (App Store Optimization), and ensure a strong app rating. Conversion Rate and AOV Optimization on App and Store : CRO Specialist - Drive initiatives to improve Conversion Rate (CVR) and Average Order Value (AOV). - Implement cross-sell and upsell strategies, leveraging customer data and behavioral insights. - Develop engaging content that complements product and service offerings. Store & App Operations Management - Manage Product Detail Pages (PDPs), Category pages, Storefronts, and Content. - Ensure accurate product and service information is displayed. - Implement dynamic pricing strategies in collaboration with category and pricing teams. - Leveraging App/Website Merchandise to drive revenue 1. Collaborate with Category, CRM, and Tech Teams to execute effective merchandising strategies. 2. Conduct A/B tests on banner placements, CTA buttons, and user flows to enhance user experience and conversion. 3. Continuously analyse and refine the customer journey using performance data. Personalized journey for Consumers on App and Website - Optimize homepages, category pages, and landing pages to maximize conversions. - Manage dynamic banners and product placements based on user behaviour and purchase history. - Develop and implement personalized product recommendations using AI- driven tools. Cross-Functional Collaboration - Align closely with the Retention, Product, Category, and Technology Teams. - Provide feedback on platform improvements to enhance user satisfaction. - Partner with the analytics team to measure campaign performance and implement data-driven decisions. Key Performance Indicators (KPIs) - App User Growth (downloads, activations, and active users) - App Feature Adoption and Engagement - App Retention and Churn Rates - Conversion Rate (CVR) and Average Order Value (AOV) - Personalization Impact on Revenue - App Store Ratings and Reviews - A/B Testing Success Metrics Qualifications: - Bachelor’s or Master’s degree in Business, Marketing, E-commerce, or a related field. - 0-3 years of experience in e-commerce operations, preferably in the healthcare or wellness sector. - Strong Problem solver, first principal thinking, strategy background with Product Understanding (Preferred) - Strong understanding of personalization platforms, A/B testing tools, and web analytics (Not mandatory) Key Competencies: - Data-driven decision-making - Customer-centric mindset - Strong analytical and problem-solving abilities - Effective communication and stakeholder management - Adaptability and continuous learning

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Bengaluru, Karnataka, India; Pune, Maharashtra, India; Hyderabad, Telangana, India . Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience with software development in one or more programming languages. 3 years of experience testing, maintaining, or launching software products. 1 year of experience with software design and architecture. Preferred qualifications: 5 years of experience with data structures/algorithms. 1 year of experience in a technical leadership role. Experience developing accessible technologies. About the job Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. In this role, you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world. We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers. Responsibilities Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Build large-scale data processing pipelines with appropriate quality/reliability checks. Debug large-scale data pipelines. Build proper monitoring for both the health of data pipelines and quality of data. Treat access/privacy/compliance as first class operators for the data pipelines. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Bengaluru, Karnataka, India; Pune, Maharashtra, India; Hyderabad, Telangana, India . Minimum qualifications: Bachelor’s degree or equivalent practical experience. 5 years of experience with software development in one or more programming languages. 3 years of experience testing, maintaining, or launching software products. 1 year of experience with software design and architecture. Preferred qualifications: 5 years of experience with data structures/algorithms. 1 year of experience in a technical leadership role. Experience developing accessible technologies. About the job Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. In this role, you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world. We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers. Responsibilities Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies. Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Build large-scale data processing pipelines with appropriate quality/reliability checks. Debug large-scale data pipelines. Build proper monitoring for both the health of data pipelines and quality of data. Treat access/privacy/compliance as first class operators for the data pipelines. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

GE Healthcare Healthcare Information Technology Category Digital Technology / IT Mid-Career Job Id R4026614 Relocation Assistance No Location Bengaluru, Karnataka, India, 560066 Job Description Summary We are seeking a highly skilled and innovative AI Engineer with expertise in both traditional Artificial Intelligence and emerging Generative AI technologies. In this role, you will be responsible for designing, developing, and deploying intelligent systems that leverage machine learning, deep learning, and generative models to solve complex problems. You will work across the AI lifecycle—from data engineering and model development to deployment and monitoring—while also exploring GenAI applications, Agentic AI and developing agentic platforms. The ideal candidate combines strong technical acumen with a passion for experimentation, rapid prototyping, and delivering scalable AI solutions in real-world environments. GE HealthCare is a leading global medical technology and digital solutions innovator. Our purpose is to create a world where healthcare has no limits. Unlock your ambition, turn ideas into world-changing realities, and join an organization where every voice makes a difference, and every difference builds a healthier world. Job Description Job Description Roles and Responsibilities In this role, you will: Develop and fine-tune Generative AI models (e.g., LLMs, diffusion models). Design and implement machine learning models for classification, regression, clustering, and recommendation tasks. Build and maintain scalable AI pipelines for data ingestion, training, evaluation, and deployment. Collaborate with cross-functional teams to understand business needs and translate them into AI solutions. Ensure model performance, fairness, and explainability through rigorous testing and validation. Deploy models to production using MLOps tools and monitor their performance over time. Stay current with the latest research and trends in AI/ML and GenAI and evaluate their applicability to business problems. Document models, experiments, and workflows for reproducibility and knowledge sharing. Technical Skill Set Cloud & Infrastructure (AWS) Amazon SageMaker – Model training, tuning, deployment, and MLOps. Amazon Bedrock – Serverless GenAI model access and orchestration. SageMaker JumpStart – pre-trained models and GenAI templates. Prompt engineering and fine-tuning of LLMs using SageMaker or Bedrock. Programming & Scripting Python – Primary language for AI/ML development, data processing, and automation. Education Qualification Bachelor’s degree in engineering with minimum four years of experience in relevant technologies. Desired Characteristics Technical Expertise: GenAI Platforms & Models Familiarity with LLMs: like Claude (Anthropic), LLaMA (Meta), Gemini (Google), Mistral, Falcon Experience with APIs: Amazon Bedrock. Understanding of model types: encoder-decoder, decoder-only, diffusion models Design, develop, and deploy agent-based AI systems that exhibit autonomous decision-making. Integrate Generative AI (LLMs, diffusion models) into real-world applications. Prompt Engineering & Fine-Tuning Prompt design for zero-shot, few-shot, and chain-of-thought reasoning Fine-tuning and parameter-efficient tuning (LoRA, PEFT) Retrieval-Augmented Generation (RAG) design and implementation System Integration & Architecture Event-driven and serverless architectures (e.g., AWS Lambda, EventBridge) Development Frameworks LangChain, LlamaIndex. Vector databases: FAISS, Pinecone, Weaviate, Amazon OpenSearch Langgraph, Langchain Cloud & DevOps AWS (Bedrock, SageMaker, Lambda, S3), Azure (OpenAI, Functions), GCP (Vertex AI) CI/CD pipelines for GenAI workflows Security & Compliance Data privacy and governance (GDPR, HIPAA) Model safety: content filtering, moderation, hallucination control Monitoring & Optimization Model performance tracking (latency, cost, accuracy) Logging and observability (CloudWatch, Prometheus, Grafana) Cost optimization strategies for GenAI inference Collaboration & Business Alignment Working with product, legal, and compliance teams Translating business requirements into GenAI use cases Creating PoCs and scaling to production Business Acumen: Demonstrates the initiative to explore alternate technology and approaches to solving problems Skilled in breaking down problems, documenting problem statements and estimating efforts Has the ability to analyze impact of technology choices Skilled in negotiation to align stakeholders and communicate a single synthesized perspective to the scrum team. Balances value propositions for competing stakeholders. Demonstrates knowledge of the competitive environment Demonstrates knowledge of technologies in the market to help make buy vs build recommendations, scope MVPs, and to drive market timing decisions Leadership: Influences through others; builds direct and "behind the scenes" support for ideas. Pre-emptively sees downstream consequences and effectively tailors influencing strategy to support a positive outcome. Able to verbalize what is behind decisions and downstream implications. Continuously reflecting on success and failures to improve performance and decision-making. Understands when change is needed. Participates in technical strategy planning. Personal Attributes: Able to effectively direct and mentor others in critical thinking skills. Proactively engages with cross-functional teams to resolve issues and design solutions using critical thinking and analysis skills and best practices. Finds important patterns in seemingly unrelated information. Influences and energizes other toward the common vision and goal. Maintains excitement for a process and drives to new directions of meeting the goal even when odds and setbacks render one path impassable. Innovates and integrates new processes and/or technology to significantly add value to GE Healthcare. Identifies how the cost of change weighs against the benefits and advises accordingly. Proactively learns new solutions and processes to address seemingly unanswerable problems. Inclusion and Diversity GE Healthcare is an Equal Opportunity Employer where inclusion matters. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law. We expect all employees to live and breathe our behaviors: to act with humility and build trust; lead with transparency; deliver with focus, and drive ownership – always with unyielding integrity. Our total rewards are designed to unlock your ambition by giving you the boost and flexibility you need to turn your ideas into world-changing realities. Our salary and benefits are everything you’d expect from an organization with global strength and scale, and you’ll be surrounded by career opportunities in a culture that fosters care, collaboration and support. #LI-MA6 Additional Information Relocation Assistance Provided: No

Position: Senior AI/ML Engineer- NLP/Python (Please Post on Naukri with the Position as it ) Experience : 3 to 5 Years Location : Mohan Corporate Office (Work from Office Only) Job Type: Full-Time Salary: To be discussed during the interview Key Responsibilities : - Design, develop, and deploy AI/ML models for real-world applications. - Work with NLP, deep learning, and traditional ML algorithms to solve complex business problems. - Develop end-to-end ML pipelines, including data preprocessing, feature engineering, model training, and deployment. - Optimize model performance using hyperparameter tuning and model evaluation techniques. - Implement AI-driven solutions using TensorFlow, PyTorch, Scikit-learn, OpenAI APIs, Hugging Face, and similar frameworks. - Work with structured and unstructured data, performing data wrangling, transformation, and feature extraction. - Deploy models in cloud environments (AWS, Azure, or GCP) using SageMaker, Vertex AI, or Azure ML. - Collaborate with cross-functional teams to integrate AI models into production systems. - Ensure scalability, performance, and efficiency of AI/ML solutions. - Stay updated with emerging AI trends and technologies to drive innovation. Required Skills : - Strong experience in machine learning, deep learning, NLP, and AI model development. - Implement Retrieval-Augmented Generation (RAG) using vector databases - Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, and OpenAI GPT models. - Expertise in NLP techniques (Word2Vec, BERT, transformers, LLMs, text classification). - Hands-on experience with computer vision (CNNs, OpenCV, YOLO, custom object detection models). - Solid understanding of ML model deployment and MLOps (Docker, Kubernetes, CI/CD for ML models). - Experience in working with cloud platforms (AWS, Azure, GCP) for AI/ML model deployment. - Strong knowledge of SQL, NoSQL databases, and big data processing tools (PySpark, Databricks, Hadoop, Kafka, etc. - Familiarity with API development using Django, Flask, or FastAPI for AI solutions. - Strong problem-solving, analytical, and communication skills. Preferred Skills : - Experience with AI-powered chatbots and OpenAI API integration. - Exposure to LLMs (GPT, LLaMA, Falcon, etc.) for real-world applications. - Hands-on experience in generative AI models.

Role : Juniper AI SME. Experience : 6 - 8 Years. Start Date : immediate 15 Days. Location : Type : Full-time. Job Summary We are seeking a highly skilled and innovative AI Solutions Specialist to lead the design, development, and deployment of AI-driven solutions tailored to complex business challenges. The ideal candidate will be responsible for building scalable, ethical, and cutting-edge AI/ML systems, collaborating with cross-functional teams to implement intelligent solutions, and leveraging industry best practices in data science, machine learning, and cloud-native architectures. Key Responsibilities Lead the development of Data Engineering, Machine Learning (ML), and AI capabilities across the full solution lifecycle. Collaborate with project, data science, and development teams to define and implement AI/ML technical roadmaps. Engage with stakeholders to identify AI/ML opportunities aligned with business needs. Architect and implement scalable AI solutions integrated with existing systems and infrastructure. Design, train, test, and optimize machine learning models and AI algorithms. Evaluate third-party AI tools, APIs, and platforms for potential integration. Develop technical documentation, solution architecture, and proof-of-concept prototypes. Partner with data engineering teams to ensure data availability, quality, and integrity. Monitor AI models in production, ensuring continuous learning, tuning, and performance improvement. Uphold responsible AI practices, including bias mitigation, explainability, and data privacy. Communicate AI strategy and progress to both technical and business stakeholders. Continuously research and apply the latest AI trends, techniques, and tools. Work within MLOps frameworks and deployment pipelines including Docker, MLflow, and CI/CD. Technical Skills & Tools Expertise in machine learning libraries and frameworks : TensorFlow, PyTorch, Scikit-learn. Juniper AI SMEProficient in programming : Python Familiarity with AI/ML platforms : AWS SageMaker, Azure ML, Google Vertex AI, Databricks, Snowflake Infrastructure & deployment tools : Docker, Kubernetes, Terraform, Ansible, Prometheus, Grafana, ELK Data technologies : Hadoop, Spark, Kafka, SQL, NoSQL, Postgres, Cassandra, Elastic Search. CRM and enterprise systems : Salesforce Experience in data preprocessing, feature engineering, and model evaluation. Exposure to Generative AI, LLMs (e.g., GPT, diffusion models), and deep learning techniques. Experience with natural language processing (NLP), computer vision, or reinforcement learning. Knowledge of Junos OS architecture, including its operational and feature-specific nuances. Preferred Qualifications Publications, patents, or open-source contributions in AI/ML. Proven leadership in building AI systems at scale Excellent analytical, communication, and stakeholder engagement skills Experience. Minimum 6-8 years in data & analytics with strong focus on AI/ML, data platforms, and data engineering Experience in leading architecture and infrastructure for end-to-end AI/ML lifecycle management. Deep understanding of technology trends, architectures, and integration strategies in AI. Hands-on expertise in predictive modeling, NLP, deep learning, and information retrieval. (ref:hirist.tech)

About LTIMindtree LTIMindtree is a global technology consulting and digital solutions company that enables enterprises across industries to reimagine business models, accelerate innovation, and maximize growth by harnessing digital technologies. As a digital transformation partner to more than 750 clients, LTIMindtree brings extensive domain and technology expertise to help drive superior competitive differentiation, customer experiences, and business outcomes in a converging world. Powered by nearly 90,000 talented and entrepreneurial professionals across more than 30 countries, LTIMindtree — a Larsen & Toubro Group company — combines the industry-acclaimed strengths of erstwhile Larsen and Toubro Infotech and Mindtree in solving the most complex business challenges and delivering transformation at scale. For more information, please visit www.ltimindtree.com Job Title : Java Microservices Work Location: Pune, Maharashtra Duration: Full time. Job Summary Experience with backend technologies Microservice architecture Java 17 Spring Boot Vertex and Hibernate Experiences with Test driven development methodologies such as Junit BDD Experience in developing messaging and streaming service including Kafka Websphere MQ ActiveMQ Solace MQ Worked on designing and delivering following aspects in Java based microservice systems Nice to have experience with Frontend technologies HTML5 JavaScript and ReactJS Ability to solve complex problems and propose solutions Fluent English Mandatory Skills : Java, MS SQL, Spring, SpringBoot, Jpa, Microservices LTIMindtree is an equal opportunity employer that is committed to diversity in the workplace. Our employment decisions are made without regard to race, colour, creed, religion, sex (including pregnancy, childbirth or related medical conditions), gender identity or expression, national origin, ancestry, age, family-care status, veteran status, marital status, civil union status, domestic partnership status, military service, handicap or disability or history of handicap or disability, genetic information, atypical hereditary cellular or blood trait, union affiliation, affectional or sexual orientation or preference, or any other characteristic protected by applicable federal, state, or local law, except where such considerations are bona fide occupational qualifications permitted by law.

Job Summary: We are seeking a highly skilled and experienced Solution Architect & Delivery Lead to join our dynamic team. This pivotal role will be responsible for defining the technical vision, designing robust solutions, and leading the end-to-end delivery of Google Contact Center AI (CCAI) initiatives, with a primary focus on CCAI Agent Assist and Dialogflow CX . The ideal candidate possesses deep hands-on expertise in conversational AI and contact center technologies, combined with proven leadership skills to guide project teams, manage stakeholders, and ensure successful, on-time, and within-budget project delivery. You will bridge the gap between business requirements and technical implementation, translating complex needs into actionable solution architectures and overseeing their execution from concept to deployment. Key Responsibilities Solution Architecture & Design (approx. 50%): Lead discovery sessions to gather and analyze complex business requirements, translating them into comprehensive Solution Design Document and architectural designs for CCAI Agent Assist and Dialogflow solutions. Design end-to-end conversational flows, intent identification, entity extraction, and fulfillment logic using Dialogflow ES/CX for both voice and chat applications. Architect and implement CCAI Agent Assist features, including real-time sentiment analysis, knowledge base integration, smart reply suggestions, and script nudges. Define integration strategies for CCAI solutions with existing contact center platforms (e.g., Salesforce, Zendesk, Genesys, Avaya), CRM systems, backend APIs, and data sources. Evaluate and recommend appropriate Google Cloud Platform (GCP) services (e.g., Cloud Storage, Cloud Functions, BigQuery, Pub/Sub, Vertex AI) to support CCAI deployments. Develop detailed architecture diagrams, technical specifications, and design documents. Ensure solutions are scalable, secure, reliable, cost-effective, and adhere to industry best practices and compliance standards. Conduct technical feasibility studies and Proof-of-Concepts (POCs) to validate architectural approaches. Stay abreast of the latest Google CCAI developments, Generative AI capabilities (including Vertex AI Conversation), and overall contact center AI trends. Project Delivery & Leadership (approx. 50%): Lead and manage the full lifecycle of CCAI projects from initiation to deployment and post-implementation support. Develop detailed project plans, scope definitions, timelines, resource allocation, and budget estimates. Act as the primary technical point of contact for clients and internal stakeholders, ensuring clear communication and expectation management. Oversee and mentor development teams (engineers, NLU specialists, QA) throughout the project lifecycle, ensuring adherence to architectural designs and quality standards. Proactively identify and mitigate project risks, resolving technical and operational roadblocks. Implement Agile methodologies (Scrum/Kanban) to ensure efficient and iterative development cycles. Define and oversee testing strategies, including unit, integration, user acceptance, and performance testing for conversational AI solutions. Collaborate with business analysts, product owners, and operations teams to ensure seamless solution adoption and measurable business impact. Provide expert guidance and troubleshooting support for complex technical issues. Required Qualifications Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field. 15+ years of progressive experience in software development, solution architecture, or technical consulting roles. 3-5+ years of hands-on experience designing and delivering Google CCAI solutions, with significant expertise in both CCAI Agent Assist and Dialogflow (ES/CX). Deep understanding of Natural Language Understanding (NLU), Natural Language Generation (NLG), and conversational AI principles. Proven experience integrating Dialogflow solutions with various channels (e.g., Genesys, Twilio, Google Contact Center AI Partner Integrations). Strong proficiency in at least one programming language (e.g., Python, Node.js, Java) for custom integrations and fulfillment logic. Extensive experience with Google Cloud Platform (GCP) services, particularly those relevant to AI/ML and data pipelines. Demonstrated experience leading complex, cross-functional technical projects from concept to completion. Excellent communication, presentation, and interpersonal skills with the ability to articulate complex technical concepts to non-technical stakeholders. Strong analytical, problem-solving, and decision-making abilities. Preferred Qualifications Master's degree in a relevant field. Google Cloud Professional Cloud Architect or Machine Learning Engineer certification. Experience with other Google AI services (e.g., Text-to-Speech, Speech-to-Text, Vertex AI). Familiarity with other contact center technologies and CRM platforms (e.g., Salesforce Service Cloud, Zendesk). Experience with pre-sales activities, including solutioning, effort estimation, and presenting to clients. Understanding of IT security, data privacy (e.g., GDPR, CCPA), and compliance best practices in a contact center context. Experience working in an Agile/Scrum environment.

Job Summary: We are seeking an experienced and highly motivated Delivery Lead to spearhead the successful implementation of Google Contact Center AI (CCAI) solutions, with a strong emphasis on CCAI Agent Assist and Dialogflow (ES/CX) . This role is critical in bridging the gap between solution design and technical execution. The Delivery Lead will be responsible for leading project teams, managing client relationships, and ensuring the on-time, on-budget, and high-quality delivery of complex conversational AI and agent augmentation projects. You will act as the primary point of contact for project stakeholders, proactively identifying and mitigating risks, and ensuring that strategic objectives are met through technical excellence. Key Responsibilities Project Leadership & Management (60%): Lead the full lifecycle of CCAI projects from initiation and planning through execution, monitoring, control, and closure. Develop and manage comprehensive project plans, including scope definition, detailed timelines, resource allocation, and budget tracking. Serve as the primary client contact for project delivery, establishing strong relationships, managing expectations, and providing regular progress updates. Lead and motivate diverse project teams (Solution Architects, NLU Specialists, Engineers, QA Analysts), fostering a collaborative and high-performing environment. Proactively identify, assess, and mitigate project risks and issues, implementing contingency plans to ensure successful outcomes. Manage project scope changes effectively, ensuring proper documentation and communication to all stakeholders. Conduct regular internal and external project review meetings, preparing and presenting status reports to senior management and clients. Ensure projects adhere to defined quality standards, best practices, and governance frameworks (e.g., Agile/Scrum). Technical Oversight & Quality Assurance (30%): Understand and validate the technical solution architecture for CCAI Agent Assist and Dialogflow, ensuring it aligns with client requirements and business objectives. Provide technical guidance and oversight to the engineering and development teams, ensuring adherence to design specifications and best practices for NLU and conversational AI. Specifically oversee the implementation of Dialogflow agents (intents, entities, flows, fulfillment logic) and CCAI Agent Assist features (real-time knowledge base integration, smart reply suggestions, sentiment analysis, script nudges). Ensure seamless integration of CCAI solutions with existing contact center platforms (e.g., Genesys, Twilio, Salesforce Service Cloud, Zendesk) and enterprise systems. Work closely with QA to define comprehensive testing strategies (unit, integration, UAT, performance) for conversational AI flows and agent assistance capabilities. Facilitate technical problem-solving during project execution, collaborating with architects and engineers to overcome complex challenges. Ensure solutions are built for scalability, security, reliability, and maintainability. Stakeholder Management & Communication (10%): Translate technical concepts and project updates into clear, concise language for non-technical stakeholders and business leadership. Negotiate and resolve conflicts effectively, maintaining positive client relationships. Collaborate with pre-sales teams to refine project scope and estimates during the planning phase. Facilitate knowledge transfer and training for client teams post-deployment, ensuring successful adoption and ongoing support. Required Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. 12+ years of experience in technical project management, delivery leadership, or a similar client-facing role. 3-5+ years of demonstrable experience leading the delivery of Google Cloud-based AI solutions, with specific hands-on project experience involving: Google CCAI Agent Assist (critical) Google Dialogflow (ES and/or CX) (critical) Strong understanding of conversational AI principles, NLU, and contact center operations. Proven experience managing complex projects with cross-functional technical teams. Familiarity with core Google Cloud Platform (GCP) services relevant to AI deployments (e.g., Cloud Functions, BigQuery, Pub/Sub). Experience with Agile/Scrum methodologies and tools (e.g., Jira, Confluence). Exceptional leadership, communication, interpersonal, and presentation skills (both written and verbal). Strong analytical, problem-solving, and negotiation abilities. Proven ability to manage multiple projects concurrently and adapt to changing priorities. Preferred Qualifications Master's degree or PMP/Agile certification (CSM, PMI-ACP). Google Cloud Certification (e.g., Professional Cloud Architect, Professional Collaboration Engineer). Hands-on experience with contact center platforms beyond CCAI (e.g., Genesys, Avaya, Cisco, Five9). Experience with other Google AI services (e.g., Speech-to-Text, Text-to-Speech, Vertex AI, Gemini models) and understanding of their integration potential. Technical background in software development (e.g., Python, Node.js) to understand implementation complexities. Experience in pre-sales activities, including solution scoping and effort estimation. Understanding of data privacy and security best practices in a contact center environment.

Job Summary: We are seeking a highly skilled and experienced Solution Architect & Delivery Lead to join our dynamic team. This pivotal role will be responsible for defining the technical vision, designing robust solutions, and leading the end-to-end delivery of Google Contact Center AI (CCAI) initiatives, with a primary focus on CCAI Agent Assist and Dialogflow CX . The ideal candidate possesses deep hands-on expertise in conversational AI and contact center technologies, combined with proven leadership skills to guide project teams, manage stakeholders, and ensure successful, on-time, and within-budget project delivery. You will bridge the gap between business requirements and technical implementation, translating complex needs into actionable solution architectures and overseeing their execution from concept to deployment. Key Responsibilities Solution Architecture & Design (approx. 50%): Lead discovery sessions to gather and analyze complex business requirements, translating them into comprehensive Solution Design Document and architectural designs for CCAI Agent Assist and Dialogflow solutions. Design end-to-end conversational flows, intent identification, entity extraction, and fulfillment logic using Dialogflow ES/CX for both voice and chat applications. Architect and implement CCAI Agent Assist features, including real-time sentiment analysis, knowledge base integration, smart reply suggestions, and script nudges. Define integration strategies for CCAI solutions with existing contact center platforms (e.g., Salesforce, Zendesk, Genesys, Avaya), CRM systems, backend APIs, and data sources. Evaluate and recommend appropriate Google Cloud Platform (GCP) services (e.g., Cloud Storage, Cloud Functions, BigQuery, Pub/Sub, Vertex AI) to support CCAI deployments. Develop detailed architecture diagrams, technical specifications, and design documents. Ensure solutions are scalable, secure, reliable, cost-effective, and adhere to industry best practices and compliance standards. Conduct technical feasibility studies and Proof-of-Concepts (POCs) to validate architectural approaches. Stay abreast of the latest Google CCAI developments, Generative AI capabilities (including Vertex AI Conversation), and overall contact center AI trends. Project Delivery & Leadership (approx. 50%): Lead and manage the full lifecycle of CCAI projects from initiation to deployment and post-implementation support. Develop detailed project plans, scope definitions, timelines, resource allocation, and budget estimates. Act as the primary technical point of contact for clients and internal stakeholders, ensuring clear communication and expectation management. Oversee and mentor development teams (engineers, NLU specialists, QA) throughout the project lifecycle, ensuring adherence to architectural designs and quality standards. Proactively identify and mitigate project risks, resolving technical and operational roadblocks. Implement Agile methodologies (Scrum/Kanban) to ensure efficient and iterative development cycles. Define and oversee testing strategies, including unit, integration, user acceptance, and performance testing for conversational AI solutions. Collaborate with business analysts, product owners, and operations teams to ensure seamless solution adoption and measurable business impact. Provide expert guidance and troubleshooting support for complex technical issues. Required Qualifications Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field. 15+ years of progressive experience in software development, solution architecture, or technical consulting roles. 3-5+ years of hands-on experience designing and delivering Google CCAI solutions, with significant expertise in both CCAI Agent Assist and Dialogflow (ES/CX). Deep understanding of Natural Language Understanding (NLU), Natural Language Generation (NLG), and conversational AI principles. Proven experience integrating Dialogflow solutions with various channels (e.g., Genesys, Twilio, Google Contact Center AI Partner Integrations). Strong proficiency in at least one programming language (e.g., Python, Node.js, Java) for custom integrations and fulfillment logic. Extensive experience with Google Cloud Platform (GCP) services, particularly those relevant to AI/ML and data pipelines. Demonstrated experience leading complex, cross-functional technical projects from concept to completion. Excellent communication, presentation, and interpersonal skills with the ability to articulate complex technical concepts to non-technical stakeholders. Strong analytical, problem-solving, and decision-making abilities. Preferred Qualifications Master's degree in a relevant field. Google Cloud Professional Cloud Architect or Machine Learning Engineer certification. Experience with other Google AI services (e.g., Text-to-Speech, Speech-to-Text, Vertex AI). Familiarity with other contact center technologies and CRM platforms (e.g., Salesforce Service Cloud, Zendesk). Experience with pre-sales activities, including solutioning, effort estimation, and presenting to clients. Understanding of IT security, data privacy (e.g., GDPR, CCPA), and compliance best practices in a contact center context. Experience working in an Agile/Scrum environment.

We are seeking a skilled DevOps Engineer with strong experience in Google Cloud Platform (GCP) to support AI/ML project infrastructure. The ideal candidate will work closely with data scientists, ML engineers, and developers to build and manage scalable, secure, and automated pipelines for AI/ML model training, testing, and deployment. Responsibilities: Design and manage cloud infrastructure to support AI/ML workloads on GCP. Develop and maintain CI/CD pipelines for ML models and applications. Automate model training, validation, deployment, and monitoring processes using tools like Kubeflow, Vertex AI, Cloud Composer, Airflow, etc. Set up and manage infrastructure as code (IaC) using tools such as Terraform or Deployment Manager. Implement robust security, monitoring, logging, and alerting systems using Cloud Monitoring, Cloud Logging, Prometheus, Grafana, etc. Collaborate with ML engineers and data scientists to optimize compute environments (e.g., GPU/TPU instances, notebooks). Manage and maintain containerized environments using Docker and Kubernetes (GKE). Ensure cost-efficient cloud resource utilization and governance. Required Skills Bachelor's degree in engineering or relevant field Must have 4 years of proven experience as DevOps Engineer with at least 1 year on GCP Strong experience with DevOps tools and methodologies in production environments Proficiency in scripting with Python, Bash, or Shell Experience with Terraform, Ansible, or other IaC tools. Deep understanding of Docker, Kubernetes, and container orchestration Knowledge of CI/CD pipelines, automated testing, and model deployment best practices. Familiarity with ML lifecycle tools such as MLflow, Kubeflow Pipelines, or TensorFlow Extended (TFX). Experience in designing conversational flows for AI Agents/chatbot

Position Overview Job Title: AI Lead , VP Location: Pune, India Role Description Engineer is responsible for managing or performing work across multiple areas of the bank's overall IT Platform/Infrastructure including analysis, development, and administration. It may also involve taking functional oversight of engineering delivery for specific departments. Work includes: Planning and developing entire engineering solutions to accomplish business goals Building reliability and resiliency into solutions with appropriate testing and reviewing throughout the delivery lifecycle Ensuring maintainability and reusability of engineering solutions Ensuring solutions are well architected and can be integrated successfully into the end-to-end business process flow Reviewing engineering plans and quality to drive re-use and improve engineering capability Participating in industry forums to drive adoption of innovative technologies, tools and solutions in the Bank. Deutsche Bank’s Corporate Bank division is a leading provider of cash management, trade finance and securities finance. We complete green-field projects that deliver the best Corporate Bank - Securities Services products in the world. Our team is diverse, international, and driven by shared focus on clean code and valued delivery. At every level, agile minds are rewarded with competitive pay, support, and opportunities to excel. You will work as part of a cross-functional agile delivery team. You will bring an innovative approach to software development, focusing on using the latest technologies and practices, as part of a relentless focus on business value. You will be someone who sees engineering as team activity, with a predisposition to open code, open discussion and creating a supportive, collaborative environment. You will be ready to contribute to all stages of software delivery, from initial analysis right through to production support. What We’ll Offer You As part of our flexible scheme, here are just some of the benefits that you’ll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your Key Responsibilities Proven ability to design, build, and deploy end-to-end AI/ML systems in production. Expertise in data science, including statistical analysis, experimentation, and data storytelling. Experienced in working with large-scale, real-world datasets for model training and analysis. Comfortable navigating urgency, ambiguity, and fast-changing priorities. Skilled at solving complex ML problems independently, from idea to implementation. Strong leadership experience building and guiding high-performing AI teams. Hands-on with deep learning, NLP, LLMs, and classical ML techniques. Fluent in model experimentation, tuning, optimisation, and evaluation at scale. Solid software engineering background and comfort working with data and full-stack teams. Experience with cloud platforms (GCP, AWS, Azure) and production-grade ML pipelines. Bias for action — willing to jump into code, data, or ops to ship impactful AI products. Your Skills And Experience PhD in Computer Science, Data Science, Machine Learning, AI, or a related field. Strong programming skills in Python (preferred), with experience in Java, Scala, or Go a plus. Deep expertise with ML frameworks like TensorFlow, PyTorch, Scikit-learn. Experience with large-scale datasets, distributed data processing (e.g. Spark, Beam, Airflow). Solid foundation in data science: statistical modeling, A/B testing, time series, and experimentation. Proficient in NLP, deep learning, and working with transformer-based LLMs. Experience with MLOps practices — CI/CD, model serving, monitoring, and lifecycle management. Hands-on with cloud platforms (GCP, AWS, Azure) and tools like Vertex AI, SageMaker, or Databricks. Strong grasp of API design, system integration, and delivering AI features in full-stack products. Comfortable working with SQL/NoSQL, and data warehouses like BigQuery or Snowflake. Familiar with ethical AI, model explainability, and secure, privacy-aware AI development How We’ll Support You Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About Us And Our Teams Please visit our company website for further information: https://www.db.com/company/company.htm We strive for a culture in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment.

Key Responsibilities AI Model Deployment & Integration: Deploy and manage AI/ML models, including traditional machine learning and GenAI solutions (e.g., LLMs, RAG systems). Implement automated CI/CD pipelines for seamless deployment and scaling of AI models. Ensure efficient model integration into existing enterprise applications and workflows in collaboration with AI Engineers. Optimize AI infrastructure for performance and cost efficiency in cloud environments (AWS, Azure, GCP). Monitoring & Performance Management: Develop and implement monitoring solutions to track model performance, latency, drift, and cost metrics. Set up alerts and automated workflows to manage performance degradation and retraining triggers. Ensure responsible AI by monitoring for issues such as bias, hallucinations, and security vulnerabilities in GenAI outputs. Collaborate with Data Scientists to establish feedback loops for continuous model improvement. Automation & MLOps Best Practices: Establish scalable MLOps practices to support the continuous deployment and maintenance of AI models. Automate model retraining, versioning, and rollback strategies to ensure reliability and compliance. Utilize infrastructure-as-code (Terraform, CloudFormation) to manage AI pipelines. Security & Compliance: Implement security measures to prevent prompt injections, data leakage, and unauthorized model access. Work closely with compliance teams to ensure AI solutions adhere to privacy and regulatory standards (HIPAA, GDPR). Regularly audit AI pipelines for ethical AI practices and data governance. Collaboration & Process Improvement: Work closely with AI Engineers, Product Managers, and IT teams to align AI operational processes with business needs. Contribute to the development of AI Ops documentation, playbooks, and best practices. Continuously evaluate emerging GenAI operational tools and processes to drive innovation. Qualifications & Skills Education: Bachelors or Masters degree in Computer Science, Data Engineering, AI, or a related field. Relevant certifications in cloud platforms (AWS, Azure, GCP) or MLOps frameworks are a plus. Experience: 3+ years of experience in AI/ML operations, MLOps, or DevOps for AI-driven solutions. Hands-on experience deploying and managing AI models, including LLMs and GenAI solutions, in production environments. Experience working with cloud AI platforms such as Azure AI, AWS SageMaker, or Google Vertex AI. Technical Skills: Proficiency in MLOps tools and frameworks such as MLflow, Kubeflow, or Airflow. Hands-on experience with monitoring tools (Prometheus, Grafana, ELK Stack) for AI performance tracking. Experience with containerization and orchestration tools (Docker, Kubernetes) to support AI workloads. Familiarity with automation scripting using Python, Bash, or PowerShell. Understanding of GenAI-specific operational challenges such as response monitoring, token management, and prompt optimization. Knowledge of CI/CD pipelines (Jenkins, GitHub Actions) for AI model deployment. Strong understanding of AI security principles, including data privacy and governance considerations.

An Amazing Career Opportunity for AI/ML Engineer Location: Chennai, India (Hybrid) Job ID: 39477 Profile Summary: We are committed to leveraging Artificial Intelligence to develop innovative solutions that enhance the experiences of both our internal and external customers. Our objective is to harness our internal knowledge base and integrate it seamlessly with business applications, enabling the delivery of intelligent, user-centric digital experiences. We are seeking a highly skilled AI/ML Engineer with a passion for continuous learning and staying ahead of emerging technologies. The ideal candidate will be instrumental in designing, developing, and scaling AI-powered solutions that address dynamic business challenges and evolving customer expectations. About HID Global HID Global powers the trusted identities of the world’s people, places and things. We make it possible for people to transact safely, work productively and travel freely. Our trusted identity solutions give people secure and convenient access to physical and digital places and connect things that can be accurately identified, verified and tracked digitally. Millions of people around the world use HID products and services to navigate their everyday lives, and over 2 billion things are connected through HID. We work with governments, educational institutions, hospitals, financial institutions, industrial businesses, and some of the most innovative companies on the planet. Headquartered in Austin, Texas, HID Global has over 4500 employees worldwide and operates international offices that support more than 100 countries. HID Global® is an ASSA ABLOY Group brand. HID Global has is the trusted source for secure identity solutions for millions of customers and users around the world. In India, we have two Engineering Centre (Bangalore and Chennai). Global Engineering Team is based in Chennai and one of the Business Unit Engineering team is based in Bangalore. Check us out: www.hidglobal.com and https://youtu.be/23km5H4K9Eo LinkedIn: www.linkedin.com/company/hidglobal/mycompany/ Physical Access Control Solutions (PACS): HID Physical Access Control Solutions (PACS) is at the forefront of securing spaces with advanced, reliable access control solutions. From cutting-edge readers, credentials and controllers to mobile and biometric technologies, HID PACS empowers organizations worldwide to protect their people, property and assets with scalable, high-quality solutions. This is more than just a job – it’s your chance to join an industry leader to drive innovation in access control and make a real impact on global security solutions. Are you ready to make a difference? Join us and help shape the future of security. Are You Ready to Join the Team? Our company is committed to finding the best and the brightest talent to help us reach the top. If you are a dynamic, highly skilled, experienced Cloud engineer and technology enthusiast, and you enjoy working in a rapid pace within a rapidly growing business environment, then you will want to consider this position. If you excel at communication, collaboration, and unrelenting innovation, we want to talk to you. And if you bring dedication, positive energy and integrity to the table, you just might be the right fit for our team. Qualifications To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Roles & Responsibilities (Other Duties May Be Assigned) Design, develop, and deploy robust & scalable AI/ML models in Production environments. Collaborate with business stakeholders to identify AI/ML opportunities and define measurable success metrics. Lead the complete software development lifecycle, from initial concept and requirements gathering to deployment and post-release support. Manage end-to-end development of software and applications, ensuring alignment with business and user needs. Design, develop, analyze, and deploy high-quality software solutions in a timely manner. Implement automated testing strategies and provide structured feedback to stakeholders throughout the development process. Integrate Multimodal Conversational AI platforms (MCP) including voice, vision, and text to deliver rich user interactions. Maintain and enhance existing software systems by diagnosing issues, implementing improvements, and verifying changes through testing. Ensure ongoing software performance, stability, and scalability through regular updates and upgrades post-deployment. Work closely with data engineers, software developers, and domain experts to integrate AI into existing systems. Conduct AI/ML training sessions for internal teams to improve AI literacy within the organization. Strong analytical and problem-solving mindset. Technical Requirements: Front-End Development: Proficiency in JavaScript/TypeScript, HTML5, CSS3, and experience with modern front-end frameworks and libraries such as Svelte or React. Proficiency in Python and hands-on experience in using ML frameworks (tensorflow, pytorch, scikit-learn, xgboost etc) Cloud-based AI/ML experience (AWS Sagemaker, Azure ML, GCP Vertex AI, etc.). Server-Side Development: Strong working knowledge of server-side programming languages, including Python and Node.js. Databases and Caching: Familiarity with relational and non-relational database systems such as SQL Server, Oracle, MySQL, and MongoDB, along with experience in caching technologies like Redis and Memcached. Solid understanding of AI/ML life cycle – Data preprocessing, feature engineering, model selection, training, validation and deployment. Artificial Intelligence / LLM: Exposure to AI and Large Language Model development using tools such as LangChain, prompt engineering techniques, and Retrieval-Augmented Generation (RAG). DevOps and CI/CD: Experience with DevOps practices, including tools and processes for continuous integration and continuous deployment (CI/CD). Security: Solid understanding of security best practices and principles related to web application development. Experience and/or Education Qualification: Graduation or master’s in computer science or information technology or AI/ML 3+ years of hands-on experience in AI/ML development/deployment and optimization Experience in LLM (RAG, prompt engineering etc) would be preferred Why apply? Empowerment: You’ll work as part of a global team in a flexible work environment, learning and enhancing your expertise. We welcome an opportunity to meet you and learn about your unique talents, skills, and experiences. You don’t need to check all the boxes. If you have most of the skills and experience, we want you to apply. Innovation: You embrace challenges and want to drive change. We are open to ideas, including flexible work arrangements, job sharing or part-time job seekers. Integrity: You are results-orientated, reliable, and straightforward and value being treated accordingly. We want all our employees to be themselves to feel appreciated and accepted. This opportunity may be open to flexible working arrangements. HID is an Equal Opportunity/Affirmative Action Employer – Minority/Female/Disability/Veteran/Gender Identity/Sexual Orientation. We make it easier for people to get where they want to go! On an average day, think of how many times you tap, twist, tag, push or swipe to get access, find information, connect with others or track something. HID technology is behind billions of interactions, in more than 100 countries. We help you create a verified, trusted identity that can get you where you need to go – without having to think about it. When you join our HID team, you’ll also be part of the ASSA ABLOY Group, the global leader in access solutions. You’ll have 63,000 colleagues in more than 70 different countries. We empower our people to build their career around their aspirations and our ambitions – supporting them with regular feedback, training, and development opportunities. Our colleagues think broadly about where they can make the most impact, and we encourage them to grow their role locally, regionally, or even internationally. As we welcome new people on board, it’s important to us to have diverse, inclusive teams, and we value different perspectives and experiences.

An Amazing Career Opportunity for AI/ML Engineer Location: Chennai, India (Hybrid) Job ID: 39582 Position Summary A rewarding career at HID Global beckons you! We are looking for an AI/ML Engineer , who is responsible for designing, developing, and deploying advanced AI/ML solutions to solve complex business challenges. This role requires expertise in machine learning, deep learning, MLOps, and AI model optimization , with a focus on building scalable, high-performance AI systems. As an AI/ML Engineer , you will work closely with data engineers, software developers, and business stakeholders to integrate AI-driven insights into real-world applications. You will be responsible for model development, system architecture, cloud deployment, and ensuring responsible AI adoption . We are a leading company in the trusted source for innovative HID Global Human Resources products, solutions and services that help millions of customers around the globe create, manage and use secure identities. Who are we? HID powers the trusted identities of the world’s people, places, and things, allowing people to transact safely, work productively and travel freely. We are a high-tech software company headquartered in Austin, TX, with over 4,000 worldwide employees. Check us out: www.hidglobal.com and https://youtu.be/23km5H4K9Eo LinkedIn: www.linkedin.com/company/hidglobal/mycompany/ About HID Global, Chennai HID Global powers the trusted identities of the world’s people, places and things. We make it possible for people to transact safely, work productively and travel freely. Our trusted identity solutions give people secure and convenient access to physical and digital places and connect things that can be accurately identified, verified and tracked digitally. Millions of people around the world use HID products and services to navigate their everyday lives, and over 2 billion things are connected through HID technology. We work with governments, educational institutions, hospitals, financial institutions, industrial businesses and some of the most innovative companies on the planet. Headquartered in Austin, Texas, HID Global has over 3,000 employees worldwide and operates international offices that support more than 100 countries. HID Global® is an ASSA ABLOY Group brand. For more information, visit www.hidglobal.com . HID Global has is the trusted source for secure identity solutions for millions of customers and users around the world. In India, we have two Engineering Centre (Bangalore and Chennai) over 200+ Engineering Staff. Global Engineering Team is based in Chennai and one of the Business Unit Engineering team is based in Bangalore. Physical Access Control Solutions (PACS) HID's Physical Access Control Solutions Business Area: HID PAC’s Business Unit focuses on the growth of new clients and existing clients where we leverage the latest card and reader technologies to solve the security challenges of our clients. Other areas of focus will include authentication, card sub systems, card encoding, Biometrics, location services and all other aspects of a physical access control infrastructure. Qualifications:- To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Roles & Responsibilities: Design, develop, and deploy robust & scalable AI/ML models in Production environments. Collaborate with business stakeholders to identify AI/ML opportunities and define measurable success metrics. Design and build Retrieval-Augmented Generation (RAG) pipelines integrating vector stores, semantic search, and document parsing for domain-specific knowledge retrieval. Integrate Multimodal Conversational AI platforms (MCP) including voice, vision, and text to deliver rich user interactions. Drive innovation through PoCs, benchmarking, and experiments with emerging models and architectures. Optimize models for performance, latency and scalability. Build data pipelines and workflows to support model training and evaluation. Conduct research & experimentation on the state-of-the-art techniques (DL, NLP, Time series, CV) Partner with MLOps and DevOps teams to implement best practices in model monitoring, version and re-training. Lead code reviews, architecture discussions and mentor junior & peer engineers. Architect and implement end-to-end AI/ML pipelines, ensuring scalability and efficiency. Deploy models in cloud-based (AWS, Azure, GCP) or on-premises environments using tools like Docker, Kubernetes, TensorFlow Serving, or ONNX Ensure data integrity, quality, and preprocessing best practices for AI/ML model development. Ensure compliance with AI ethics guidelines, data privacy laws (GDPR, CCPA), and corporate AI governance. Work closely with data engineers, software developers, and domain experts to integrate AI into existing systems. Conduct AI/ML training sessions for internal teams to improve AI literacy within the organization. Strong analytical and problem solving mindset. Technical Requirements: Strong expertise in AI/ML engineering and software development. Strong experience with RAG architecture, vector databases Proficiency in Python and hands-on experience in using ML frameworks (tensorflow, pytorch, scikit-learn, xgboost etc) Familiarity with MCPs like Google Dialogflow, Rasa, Amazon Lex, or custom-built agents using LLM orchestration. Cloud-based AI/ML experience (AWS Sagemaker, Azure ML, GCP Vertex AI, etc.). Solid understanding of AI/ML life cycle – Data preprocessing, feature engineering, model selection, training, validation and deployment. Experience in production grade ML systems (Model serving, APIs, Pipelines) Familiarity with Data engineering tools (SPARK, Kafka, Airflow etc) Strong knowledge of statistical modeling, NLP, CV, Recommendation systems, Anomaly detection and time series forecasting. Hands-on in Software engineering with knowledge of version control, testing & CI/CD Hands-on experience in deploying ML models in production using Docker, Kubernetes, TensorFlow Serving, ONNX, and MLflow. Experience in MLOps & CI/CD for ML pipelines, including monitoring, retraining, and model drift detection. Proficiency in scaling AI solutions in cloud environments (AWS, Azure & GCP). Experience in data preprocessing, feature engineering, and dimensionality reduction. Exposure to Data privacy, Compliance and Secure ML practices Education and/or Experience: Graduation or master’s in computer science or information technology or AI/ML/Data science 3+ years of hands-on experience in AI/ML development/deployment and optimization Experience in leading AI/ML teams and mentoring junior engineers. Why apply? Empowerment: You’ll work as part of a global team in a flexible work environment, learning and enhancing your expertise. We welcome an opportunity to meet you and learn about your unique talents, skills, and experiences. You don’t need to check all the boxes. If you have most of the skills and experience, we want you to apply. Innovation: You embrace challenges and want to drive change. We are open to ideas, including flexible work arrangements, job sharing or part-time job seekers. Integrity: You are results-orientated, reliable, and straightforward and value being treated accordingly. We want all our employees to be themselves, to feel appreciated and accepted. This opportunity may be open to flexible working arrangements. HID is an Equal Opportunity/Affirmative Action Employer – Minority/Female/Disability/Veteran/Gender Identity/Sexual Orientation. We make it easier for people to get where they want to go! On an average day, think of how many times you tap, twist, tag, push or swipe to get access, find information, connect with others or track something. HID technology is behind billions of interactions, in more than 100 countries. We help you create a verified, trusted identity that can get you where you need to go – without having to think about it. When you join our HID team, you’ll also be part of the ASSA ABLOY Group, the global leader in access solutions. You’ll have 63,000 colleagues in more than 70 different countries. We empower our people to build their career around their aspirations and our ambitions – supporting them with regular feedback, training, and development opportunities. Our colleagues think broadly about where they can make the most impact, and we encourage them to grow their role locally, regionally, or even internationally. As we welcome new people on board, it’s important to us to have diverse, inclusive teams, and we value different perspectives and experiences.

Job Description As the Machine Learning Enablement Engineering Manager within Ford’s Data Platforms and Engineering (DP&E) organization, you are a key leader responsible for guiding and developing a team of engineers focused on delivering high-impact, scalable machine learning solutions to address critical business challenges within DP&E. Your primary focus will be on building and maintaining the platform infrastructure and processes that empower data scientists and ML engineers to rapidly deploy and scale their solutions into production. You will work closely with Product Managers, Architects, Data Scientists, and other key stakeholders to drive engineering excellence, promote innovation, and uphold best practices. This role is less about building individual ML models and more about creating robust, reliable, and scalable solutions that allow others to deliver value effectively. Your leadership is crucial in driving the success of our machine learning initiatives. Your ability to guide and develop a team of engineers, while maintaining alignment with Ford’s strategic goals, will be key to delivering world-class, production-ready ML solutions that power Ford’s transformation into a data-driven enterprise. You should be a highly hands-on engineering leader with a proven track record of delivering complex, scalable solutions. While a deep understanding of ML concepts is beneficial, your primary focus will be on platform engineering, DevOps, and building robust, maintainable infrastructure. You will define processes for technical platforms, conceive application prototypes, and mentor your team in best practices. Your day-to-day responsibilities will involve designing and managing the organization's ML infrastructure architecture, ensuring data is efficiently processed, stored, and accessed to support ML model development and deployment. You will be pivotal in delivering these solutions on time and within budget. Responsibilities I. Engineering Leadership & Management: Proven experience (7+ years) in a leadership role managing engineering teams, ideally with a focus on platform engineering, MLOps, or similar areas. Experience managing remote teams is a plus. Experience leading and mentoring engineering teams, fostering a culture of innovation, continuous learning, and technical excellence. Demonstrated ability to drive strategic technical decisions and ensure alignment with broader organizational goals. Proven ability to build and maintain high-performing teams, promoting accountability, ownership, and collaboration. Experience with performance management, including conducting performance reviews and providing constructive feedback. Excellent communication and interpersonal skills, with a proven ability to cultivate cross-functional collaboration and build strong relationships with stakeholders at all levels. II. Agile & Scrum Practices: Deep understanding and practical experience with Agile methodologies (Scrum, Kanban), including facilitating daily stand-ups, sprint planning, backlog grooming, and sprint retrospectives. Experience working closely with Product Managers to align engineering efforts with product goals, ensure well-defined user stories, and manage priorities effectively. Proven ability to ensure engineering rigor in story hygiene, including clear acceptance criteria, well-defined dependencies, and a focus on deliverability within the sprint. III. Technical Expertise & Accountability: Deep understanding of platform engineering principles and experience designing, building, and maintaining scalable and reliable infrastructure for ML workloads. Expertise in DevOps practices, including CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions), infrastructure-as-code (Terraform, Ansible, CloudFormation), and automation. Proficiency in at least one programming language (e.g., Python, Java) sufficient to effectively communicate with and guide your engineering team. You won’t be expected to contribute to team capacity by coding, but you need to be able to speak the language of your engineers. Strong understanding of cloud solutions and offerings (preferably GCP services – Compute Engine, Kubernetes Engine, Cloud Functions, BigQuery, Pub/Sub, Cloud Storage, Vertex AI). Experience with other major cloud providers (AWS, Azure) is also valuable. Experience with designing and implementing microservices and serverless architectures. Experience with containerization (Docker, Kubernetes) is highly beneficial. Experience with monitoring and optimizing platform performance, ensuring systems are running efficiently and meeting SLAs. Proven ability to lead incident management efforts and implement continuous improvements to enhance reliability. Commitment to best engineering practices, including code reviews, testing, and documentation. A focus on building maintainable and scalable systems is essential. IV. Operational Excellence & Cost Optimization: Proven ability to drive cost optimization initiatives, particularly in cloud infrastructure and resource usage, aligning with Ford’s broader cost-reduction goals. Experience tracking and reporting key metrics for your domain/platform related to team performance, including quality and operational efficiency. Qualifications ML Enablement Engineering

Client Type: US Client Location: Remote The hourly rate is negotiable. About the Role We’re creating a new certification: Google AI Ecosystem Architect (Gemini & DeepMind) - Subject Matter Expert . This course is designed for technical learners who want to understand and apply the capabilities of Google’s Gemini models and DeepMind technologies to build powerful, multimodal AI applications. We’re looking for a Subject Matter Expert (SME) who can help shape this course from the ground up. You’ll work closely with a team of learning experience designers, writers, and other collaborators to ensure the course is technically accurate, industry-relevant, and instructionally sound. Responsibilities As the SME, you’ll partner with learning experience designers and content developers to: Translate real-world Gemini and DeepMind applications into accessible, hands-on learning for technical professionals. Guide the creation of labs and projects that allow learners to build pipelines for image-text fusion, deploy Gemini APIs, and experiment with DeepMind’s reinforcement learning libraries. Contribute technical depth across activities, from high-level course structure down to example code, diagrams, voiceover scripts, and data pipelines. Ensure all content reflects current, accurate usage of Google’s multimodal tools and services. Be available during U.S. business hours to support project milestones, reviews, and content feedback. This role is an excellent fit for professionals with deep experience in AI/ML, Google Cloud, and a strong familiarity with multimodal systems and the DeepMind ecosystem. Essential Tools & Platforms A successful SME in this role will demonstrate fluency and hands-on experience with the following: Google Cloud Platform (GCP) Vertex AI (particularly Gemini integration, model tuning, and multimodal deployment) Cloud Functions, Cloud Run (for inference endpoints) BigQuery and Cloud Storage (for handling large image-text datasets) AI Platform Notebooks or Colab Pro Google DeepMind Technologies JAX and Haiku (for neural network modeling and research-grade experimentation) DeepMind Control Suite or DeepMind Lab (for reinforcement learning demonstrations) RLax or TF-Agents (for building and modifying RL pipelines) AI/ML & Multimodal Tooling Gemini APIs and SDKs (image-text fusion, prompt engineering, output formatting) TensorFlow 2.x and PyTorch (for model interoperability) Label Studio, Cloud Vision API (for annotation and image-text preprocessing) Data Science & MLOps DVC or MLflow (for dataset and model versioning) Apache Beam or Dataflow (for processing multimodal input streams) TensorBoard or Weights & Biases (for visualization) Content Authoring & Collaboration GitHub or Cloud Source Repositories Google Docs, Sheets, Slides Screen recording tools like Loom or OBS Studio Required skills and experience: Demonstrated hands-on experience building, deploying, and maintaining sophisticated AI powered applications using Gemini APIs/SDKs within the Google Cloud ecosystem, especially in Firebase Studio and VS Code. Proficiency in designing and implementing agent-like application patterns, including multi-turn conversational flows, state management, and complex prompting strategies (e.g., Chain-of Thought, few-shot, zero-shot). Experience integrating Gemini with Google Cloud services (Firestore, Cloud Functions, App Hosting) and external APIs for robust, production-ready solutions. Proven ability to engineer applications that process, integrate, and generate content across multiple modalities (text, images, audio, video, code) using Gemini’s native multimodal capabilities. Skilled in building and orchestrating pipelines for multimodal data handling, synchronization, and complex interaction patterns within application logic. Experience designing and implementing production-grade RAG systems, including integration with vector databases (e.g., Pinecone, ChromaDB) and engineering data pipelines for indexing and retrieval. Ability to manage agent state, memory, and persistence for multi-turn and long-running interactions. Proficiency leveraging AI-assisted coding features in Firebase Studio (chat, inline code, command execution) and using App Prototyping agents or frameworks like Genkit for rapid prototyping and structuring agentic logic. Strong command of modern development workflows, including Git/GitHub, code reviews, and collaborative development practices. Experience designing scalable, fault-tolerant deployment architectures for multimodal and agentic AI applications using Firebase App Hosting, Cloud Run, or similar serverless/cloud platforms. Advanced MLOps skills, including monitoring, logging, alerting, and versioning for generative AI systems and agents. Deep understanding of security best practices: prompt injection mitigation (across modalities), secure API key management, authentication/authorization, and data privacy. Demonstrated ability to engineer for responsible AI, including bias detection, fairness, transparency, and implementation of safety mechanisms in agentic and multimodal applications. Experience addressing ethical challenges in the deployment and operation of advanced AI systems. Proven success designing, reviewing, and delivering advanced, project-based curriculum and hands-on labs for experienced software developers and engineers. Ability to translate complex engineering concepts (RAG, multimodal integration, agentic patterns, MLOps, security, responsible AI) into clear, actionable learning materials and real world projects. 5+ years of professional experience in AI-powered application development, with a focus on generative and multimodal AI. Strong programming skills in Python and JavaScript/TypeScript; experience with modern frameworks and cloud-native development. Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI, or a related technical field. Ability to explain advanced technical concepts (e.g., fusion transformers, multimodal embeddings, RAG workflows) to learners in an accessible way. Strong programming experience in Python and experience deploying machine learning pipelines Ability to work independently, take ownership of deliverables, and collaborate closely with designers and project managers Preferred: Experience with Google DeepMind tools (JAX, Haiku, RLax, DeepMind Control Suite/Lab) and reinforcement learning pipelines. Familiarity with open data formats (Delta, Parquet, Iceberg) and scalable data engineering practices. Prior contributions to open-source AI projects or technical community engagement.

Req ID: 329860 NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization, apply now. We are currently seeking a Python API Developer to join our team in Hyderabad, Telangana (IN-TG), India (IN). "NTT DATA Services currently seeks Python API developer to join our team in Bangalore / Hyderabad The right candidate will have expert level experience in Python, Hadoop Big Data environment, Model testing, Model Deployment, Google Cloud Platform, Vertex AI and developing repeatable and predictable python based frameworks. The role will require the candidate to be the technical lead and agile developer for key model operationalization task. Responsibilities : 1. Design API and Batch applications 2. Develop Ingestion Pipelines from RDBMS to Data Lakes 3. AIML Model Testing & Model Deployment 4. Release coordination to enable safe and automated production deployments 5. Create application architecture and design documentation 6. Develop applications using agile methodologies 7. Act as agile SME for the team 8. Perform unit testing 9. Support application deployment to production 10. Interact with various teams to conduct daily work" About NTT DATA NTT DATA is a $30 billion trusted global innovator of business and technology services. We serve 75% of the Fortune Global 100 and are committed to helping clients innovate, optimize and transform for long term success. As a Global Top Employer, we have diverse experts in more than 50 countries and a robust partner ecosystem of established and start-up companies. Our services include business and technology consulting, data and artificial intelligence, industry solutions, as well as the development, implementation and management of applications, infrastructure and connectivity. We are one of the leading providers of digital and AI infrastructure in the world. NTT DATA is a part of NTT Group, which invests over $3.6 billion each year in R&D to help organizations and society move confidently and sustainably into the digital future. Visit us at us.nttdata.com NTT DATA endeavors to make https://us.nttdata.com accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact us at https://us.nttdata.com/en/contact-us. This contact information is for accommodation requests only and cannot be used to inquire about the status of applications. NTT DATA is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. For our EEO Policy Statement, please click here. If you'd like more information on your EEO rights under the law, please click here. For Pay Transparency information, please click here.

Hello, Truecaller is calling you from Bangalore, India! Ready to pick up? Our goal is to make communication smarter, safer, and more efficient, all while building trust everywhere. We're all about bringing you smart services with a big social impact, keeping you safe from fraud, harassment, scam calls or messages, so you can focus on the conversations that matter. Top 20 most downloaded apps globally, and world’s #1 caller ID and spam-blocking service for Android and iOS, with extensive AI capabilities, with more than 450 million active users per month. Founded in 2009, listed on Nasdaq OMX Stockholm and is categorized as a Large Cap. Our focus on innovation, operational excellence, sustainable growth, and collaboration has resulted in consistently high profitability and strong EBITDA margins. A team of 400 people from ~35 different nationalities spread across our headquarters in Stockholm and offices in Bangalore, Mumbai, Gurgaon and Tel Aviv with high ambitions. We in the Insights Team are responsible for SMS Categorization, Fraud detection and other Smart SMS features within the Truecaller app. The OTP & bank notifications, bill & travel reminder alerts are some examples of the Smart SMS features. The team has developed a patented offline text parser that powers all these features and the team is also exploring cutting edge technologies like LLM to enhance the Smart SMS features. The team’s mission is to become the World’s most loved and trusted SMS app which is aligned with Truecaller’s vision to make communication safe and efficient. Smart SMS is used by over 90M users every day. As an ML Engineer , you will be responsible for collecting, organizing, analyzing, and interpreting Truecaller data with a focus on NLP. In this role, you will be working hands-on to optimize the training and deployment of ML models to be quick and cost-efficient. Also, you will be pivotal in advancing our work with large language models and in-device models across diverse regions. Your expertise will enhance our natural language processing, machine learning, and predictive analytics capabilities. What You Bring In 3+ years in machine learning engineering, with hands-on involvement in feature engineering, model development, and deployment. Experience in Natural Language Processing (NLP), with a deep understanding of text processing, model development, and deployment challenges in the domain. Proven ability to develop, deploy, and maintain machine learning models in production environments, ensuring scalability, reliability, and performance. Strong familiarity with ML frameworks like TensorFlow, PyTorch, and ONNX, and experience in tech stack such as Kubernetes, Docker, APIs, Vertex AI, GCP. Experience deploying models across backend and mobile platforms. Fine-tune and optimize LLMs prompts for domain-specific applications Ability to optimize feature engineering, model training, and deployment strategies for performance and efficiency. Strong SQL and statistical skills. Programming knowledge in at least one language, such as Python or R. Preferably python. Knowledge of machine learning algorithms. Excellent teamwork and communication skills, with the ability to work cross-functionally with product, engineering, and data science teams. Good to have the knowledge in retrieval-based pipelines to enhance LLM performance The Impact You Will Create Collaborate with Product and Engineering to scope, design, and implement systems that solve complex business problems ensuring they are delivered on time and within scope. Design, develop, and deploy state-of-the-art NLP models, contributing directly to message classification and fraud detection at scale for millions of users. Leverage cutting-edge NLP techniques to enhance message understanding, spam filtering, and fraud detection, ensuring a safer and more efficient messaging experience. Build and optimize ML models that can efficiently handle large-scale data processing while maintaining accuracy and performance. Work closely with data scientists and data engineers to enable rapid experimentation, development, and productionization of models in a cost-effective manner. Streamline the ML lifecycle, from training to deployment, by implementing automated workflows, CI/CD pipelines, and monitoring tools for model health and performance. Stay ahead of advancements in ML and NLP, proactively identifying opportunities to enhance model performance, reduce latency, and improve user experience. Your work will directly impact millions of users, improving message classification, fraud detection, and the overall security of messaging platforms. It Would Be Great If You Also Have Understanding of Conversational AI Deploying NLP models in production Working knowledge of GCP components Cloud-based LLM inference with Ray, Kubernetes, and serverless architectures. Life at Truecaller - Behind the code: https://www.instagram.com/lifeattruecaller/ Sounds like your dream job? We will fill the position as soon as we find the right candidate, so please send your application as soon as possible. As part of the recruitment process, we will conduct a background check. This position is based in Bangalore , India. We only accept applications in English. What We Offer A smart, talented and agile team: An international team where ~35 nationalities are working together in several locations and time zones with a learning, sharing and fun environment. A great compensation package: Competitive salary, 30 days of paid vacation, flexible working hours, private health insurance, parental leave, telephone bill reimbursement, Udemy membership to keep learning and improving and Wellness allowance. Great tech tools: Pick the computer and phone that you fancy the most within our budget ranges. Office life: We strongly believe in the in-person collaboration and follow an office-first approach while offering some flexibility. Enjoy your days with great colleagues with loads of good stuff to learn from, daily lunch and breakfast and a wide range of healthy snacks and beverages. In addition, every now and then check out the playroom for a fun break or join our exciting parties and or team activities such as Lab days, sports meetups etc. There something for everyone! Come as you are: Truecaller is diverse, equal and inclusive. We need a wide variety of backgrounds, perspectives, beliefs and experiences in order to keep building our great products. No matter where you are based, which language you speak, your accent, race, religion, color, nationality, gender, sexual orientation, age, marital status, etc. All those things make you who you are, and that’s why we would love to meet you. Job info Location Bengaluru, Karnataka, India Category Data Science Team Insights Posted today

Company Description WNS (Holdings) Limited (NYSE: WNS), is a leading Business Process Management (BPM) company. We combine our deep industry knowledge with technology and analytics expertise to co-create innovative, digital-led transformational solutions with clients across 10 industries. We enable businesses in Travel, Insurance, Banking and Financial Services, Manufacturing, Retail and Consumer Packaged Goods, Shipping and Logistics, Healthcare, and Utilities to re-imagine their digital future and transform their outcomes with operational excellence.We deliver an entire spectrum of BPM services in finance and accounting, procurement, customer interaction services and human resources leveraging collaborative models that are tailored to address the unique business challenges of each client. We co-create and execute the future vision of 400+ clients with the help of our 44,000+ employees. Job Description Min Exp - 5-8 years Location - Remote Shift timings - 6 pm to 3 am (Night Shift) Exp with Data Drift is important Engagement & Project Overview An AI model trainer brings specialised knowledge in developing and fine-tuning machine learning models. They can ensure that your models are accurate, efficient, and tailored to your specific needs. Hiring an AI model trainer and tester can significantly enhance our data management and analytics capabilities Job Description Expertise in Model Development: Develop and fine-tune machine learning models. Ensure models are accurate, efficient, and tailored to our specific needs. 2. Quality Assurance: Rigorously evaluate models to identify and rectify errors. Maintain the integrity of our data-driven decisions through high performance and reliability. 3. Efficiency and Scalability: Streamline processes to reduce time-to-market. Scale AI initiatives and ML engineering skills effectively with dedicated model training and testing. 4. Production ML Monitoring & MLOps: Implement and maintain model monitoring pipelines to detect data drift, concept drift, and model performance degradation. Set up alerting and logging systems using tools such as Evidently AI, WhyLabs/Prometheus + Grafana or cloud-native solutions (AWS SageMaker Monitor, GCP Vertex AI, Azure Monitor ) . Collaborate with teams to integrate monitoring into CI/CD pipelines, using platforms like Kubeflow, MLflow, Airflow, and Neptune.ai. Define and manage automated retraining triggers and model versioning strategies. Ensure observability and traceability across the ML lifecycle in production environments. Qualifications Qualifications: 5+ years of experience in the respective field. Proven experience in developing and fine-tuning machine learning models. Strong background in quality assurance and model testing. Ability to streamline processes and scale AI initiatives. Innovative mindset with a keen understanding of industry trends. License/Certification/Registration