1281 Mlflow Jobs - Page 7

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)

Job Title Digital Transformation Lead, (Mumbai) About Godrej Agrovet Godrej Agrovet Limited (GAVL) is a diversified, Research & Development focused agri- business Company, dedicated to improving the productivity of Indian farmers by innovating products and services that sustainably increase crop and livestock yields. GAVL holds leading market positions in the different businesses in which it operates - Animal Feed, Crop Protection, Oil Palm, Dairy and Poultry and Processed Foods. With FY ’18- ’19 Sales of 6000 Crore INR, GAVL has a pan India presence with sales of over a million tonnes annually of high quality feed and cutting-edge nutrition products for cattle, poultry, aqua feed and specialty feed. Apart from these businesses, the Company has a joint venture with the ACI group of Bangladesh for animal feed business in Bangladesh. Godrej Agrovet has 50 manufacturing facilities across India with a network of 10,000 rural distributors/dealers and over 2500 employees. Our People Philosophy Core to our employer brand, is the philosophy of tough love. We expect a lot from our team members, differentiate on the basis of performance and potential through career opportunities and rewards and lay particular emphasis on developing, mentoring and training. We believe that passionate, rounded individuals with diverse interests make for better Godrejites. And we understand that our team members play multi-faceted roles. This is why we encourage them, not just to explore their whole selves, but also create an enabling space for them to do so. Watch ‘Why Godrej’ by Nadir Godrej, a video on our people philosophy. https://www.youtube.com/watch?v=RxiHCMR64Hs&feature=emb_logo Read more about our people philosophy here. https://godrejcareers.com/people-philosophy.aspx Yo Position Summary: As a skilled Data Scientist, you will leverage your analytical skills to uncover insights from complex datasets, build predictive models, and inform data-driven decisions across the organization. You’ll work closely with cross-functional teams, including business, engineering, and product, to apply advanced statistical methods, machine learning, and domain knowledge to solve real-world problems. Job Responsibilities Data Cleaning, Preprocessing & exploration: Prepare data for analysis, ensuring quality, consistency, and completeness by handling missing values, outliers, and transforming data. Explore and analyze large and complex datasets to identify patterns, trends, and anomalies Machine Learning Model Development: Build, train, and deploy machine learning models on the Databricks platform, leveraging tools such as MLflow for experiment with techniques like regression, classification, clustering, and time series analysis Model Evaluation & Deployment: Develop and select features to improve model performance, leveraging Databricks' distributed computing capabilities for efficient processing. Familiarity with CI/CD tools (e.g., Jenkins, GitLab) for automating deployment and testing of data pipelines Collaboration: Collaborate with data engineers, analysts, and business stakeholders to understand business requirements and translate them into data-driven solutions. Data Visualization and Reporting: Create visualizations and dashboards within Databricks, Power BI and other tools to communicate insights to technical and non-technical stakeholders. Continuous Learning: Stay up to date with the latest developments in data science, machine learning, and industry best practices to continually enhance skills and processes. Technical Skills Knowledge of statistical analysis techniques, hypothesis testing, and machine learning Familiarity with NLP, time series analysis, and computer vision or A/B testing Databricks and Apache Spark: Proficiency with Databricks, Spark DataFrames and MLlib Programming: Proficiency in (Python, TensorFlow, Pandas, scikit-learn, PySpark, NumPy) with experience in writing scalable code for large datasets SQL: Strong SQL skills for data extraction, manipulation, and analysis Familiarity with MLflow for tracking, model versioning, and reproducibility. Familiarity with cloud data storage and processing tools (e.g., Azure Data Lake, AWS S3). Qualifications Education: Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related field Experience: 3+ years of experience in a data science or analytical role. Job location: Vikhroli, Mumbai.

Embark on an exciting journey into the realm of software development with 3Pillar! We extend an invitation for you to join our team and gear up for a thrilling adventure. As an AI/ML Lead, you will manage a team of data scientists, ML engineers, and developers to build AI-powered features, drive PoCs to production, and collaborate with stakeholders to deliver measurable business impact. If you are passionate about discovering solutions hidden in large data sets to improve business outcomes, consider this your pass to the captivating world of Data Science and Engineering! 🚀💻 Responsibilities Lead a team of AI ML engineers, providing technical guidance, mentorship, and support. Collaborate directly with client teams to understand business problems, explain technical solutions clearly, and lead the implementation of AI/ML features while representing 3Pillar’s technical excellence. Lead technical execution of AI/ML projects from experimentation to production. Translate business problems into AI/ML solutions and manage solution delivery. Guide team members on model selection, evaluation, fine-tuning, and Gen AI usage. Collaborate with product, data engineering, and software teams for integrated delivery. Conduct code reviews, ensure best practices, and contribute to model deployment pipelines. Maintain documentation and model governance as per responsible AI standards. Define project goals, scope, and deliverables in collaboration with stakeholders. Create scalable architecture and robust machine learning systems that meet business objectives of a software product. Collaborate with cross-functional teams to integrate machine learning solutions into existing products and workflows. Establish best practices and standards for machine learning development within the organization. Monitor and evaluate the performance of machine learning models in production and implement improvements as needed. Stay updated on industry trends and advancements in machine learning technologies. Implement, deploy, optimize AI/ML algorithms and models into production environments. Conduct experiments, perform data analysis, and present findings to stakeholders. Qualifications Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; a Master’s degree is preferred. 8+ years of experience in building AI models with ML, NLP and deep learning. Proven track record of successfully delivering machine learning projects from concept to production. Strong leadership, interpersonal skills, and ability to effectively communicate technical concepts to non-technical stakeholders. Excellent problem-solving abilities and attention to detail. Strong knowledge of AI/ML techniques, algorithms, and frameworks. Experience building and deploying ML models (classification, NLP, forecasting). Experience with cloud platforms such as AWS, Azure, or Google Cloud. Strong programming skills in Python, and familiarity with libraries such as PyTorch, TensorFlow, and Scikit-Learn. Solid understanding of machine learning concepts, algorithms, and statistical methods. Experience with computer vision libraries (OpenCV, etc.) and NLP libraries (spaCy, Hugging Face, etc.). Knowledge of MLOps practices and experience with CI/CD tools. Good understanding of using LLMs via APIs or fine-tuning open-source models. Hands-on with data prep (Pandas, Spark), feature engineering, model training and tuning. Knowledge of vector stores, embeddings, and LLMOps tools (LangChain, LlamaIndex, etc.). Experience with at least one cloud platform and CI/CD for ML (GitHub Actions, MLflow, etc.). Exposure to monitoring frameworks (evidently.ai, whylogs, or custom dashboards). Proven ability to work independently and with a team. Benefits Imagine a flexible work environment – whether it's the office, your home, or a blend of both. From interviews to onboarding, we embody a remote-first approach. You will be part of a global team, learning from top talent around the world and across cultures, speaking English everyday. Our global workforce enables our team to leverage global resources to accomplish our work in efficient and effective teams. We’re big on your well-being – as a company, we spend a whole trimester in our annual cycle focused on wellbeing. Whether it is taking advantage of fitness offerings, mental health plans (country-dependent), or simply leveraging generous time off, we want all of our team members operating at their best. Our professional services model enables us to accelerate career growth and development opportunities - across projects, offerings, and industries. We are an equal opportunity employer. It goes without saying that we live by values like Intrinsic Dignity and Open Collaboration to create cutting-edge technology AND reinforce our commitment to diversity - globally and locally. Join us and be a part of a global tech community! 🌍💼 Check out our Linkedin site and Careers page to learn more about what it’s like to be part of our #oneteam! Apply for this job

Job Overview We are seeking a highly experienced and innovative Senior AI Engineer with a strong background in Generative AI , including LLM fine-tuning and prompt engineering . This role requires hands-on expertise across NLP , Computer Vision , and AI agent-based systems , with the ability to build, deploy, and optimize scalable AI solutions using modern tools and frameworks. Required Skills & Qualifications Bachelor’s or Master’s in Computer Science, AI, Machine Learning, or related field. 5+ years of hands-on experience in AI/ML solution development. Proven expertise in fine-tuning LLMs (e.g., LLaMA, Mistral, Falcon, GPT-family) using techniques like LoRA, QLoRA, PEFT. Deep experience in prompt engineering, including zero-shot, few-shot, and retrieval-augmented generation (RAG). Proficient in key AI libraries and frameworks: LLMs & GenAI: Hugging Face Transformers, LangChain, LlamaIndex, OpenAI API, Diffusers NLP: SpaCy, NLTK. Vision: OpenCV, MMDetection, YOLOv5/v8, Detectron2 MLOps: MLflow, FastAPI, Docker, Git Familiarity with vector databases (Pinecone, FAISS, Weaviate) and embedding generation. Experience with cloud platforms like AWS, GCP, or Azure, and deployment on in house GPU-backed infrastructure. Strong communication skills and ability to convert business problems into technical solutions. Preferred Qualifications Experience building multimodal systems (text + image, etc.) Practical experience with agent frameworks for autonomous or goal-directed AI. Familiarity with quantization, distillation, or knowledge transfer for efficient model deployment. Key Responsibilities Design, fine-tune, and deploy generative AI models (LLMs, diffusion models, etc.) for real-world applications. Develop and maintain prompt engineering workflows, including prompt chaining, optimization, and evaluation for consistent output quality. Build NLP solutions for Q&A, summarization, information extraction, text classification, and more. Develop and integrate Computer Vision models for image processing, object detection, OCR, and multimodal tasks. Architect and implement AI agents using frameworks such as LangChain, AutoGen, CrewAI, or custom pipelines. Collaborate with cross-functional teams to gather requirements and deliver tailored AI-driven features. Optimize models for performance, cost-efficiency, and low latency in production. Continuously evaluate new AI research, tools, and frameworks and apply them where relevant. Mentor junior AI engineers and contribute to internal AI best practices and documentation. Skills:- Artificial Intelligence (AI), Generative AI, Machine Learning (ML), Large Language Models (LLM), Prompt engineering, Retrieval Augmented Generation (RAG), Natural Language Processing (NLP), Computer Vision, AI Agents, Vector database, Python, Docker and API

Responsibilities: Research: Stay up-to-date with the latest research in NLP/NLU space and work on various problems like topic modeling, machine translation, token classification / NER, semantic understanding and knowledge graph. Design: Take ownership for pythonic applications within the team and work independently to ensure its launch, improvement and maintenance and participate in product design discussion and decisions. Implement: Enhance current product features and proactively develop new features which have a reasonable value proposition for the end-user and suggest improvement and optimizations in deployed algorithms and implement the same while participating in agile development. Collaborate: Partner with product managers to make data driven decisions and help solve problems for end-users as well as other data science teams to establish and follow organizational best practices. Leadership: Perform technical reviews and bring overall leadership within the team and provide mentorship and training to junior team members. Requirements: B.Tech / M.Tech from a top-tier engineering college with a strong mathematical background. 3+ years of experience in Machine learning, 2+ years of experience working with NLP/NLU based technologies. Experience in machine / deep learning frameworks such as TensorFlow, Keras, Pytorch and good knowledge of CNN, RNN/LSTM/GRU, Transformer Models, Transfer Learning, Ensemble Learning as well as classical ML techniques like LDA, SVD and Clustering. Strong Python programming skills and familiarity with back-end development / devops-Flask, uWSGI, MySQL, Celery, Docker will be a plus. Bonus: Prior experience with AWS related services and familiarity with platforms like MLFlow for managing ML lifecycle and experimentation. Strong problem solving skills and readiness to learn new concepts and apply them to find practical solutions to complex problems Ability to work in a fast-paced start up with strict deadlines Reasonable communication and teamwork skills

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: About Us: At Optum AI, we leverage data and resources to make a significant impact on the healthcare system. Our solutions have the potential to improve healthcare for everyone. We work on cutting-edge projects involving ML, NLP, and LLM techniques, continuously developing and improving generative AI methods for structured and unstructured healthcare data. Our team collaborates with world-class experts and top universities to develop innovative AI/ML solutions, often leading to patents and published papers. Primary Responsibilities: Develop and implement AI and machine learning strategies for several healthcare domains Hands on Experience in AI and drive the development of innovative AI and machine learning solutions Collaborate with cross-functional teams to identify and prioritize AI and machine learning initiatives Manage the development and deployment of AI and machine learning solutions Develop and run pipelines for data ingress and model output egress. Develop and run scripts for ML model inference. Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions. Identify technical problems and develop software updates and fixes. Develop scripts or tools to automate repetitive tasks. Automate the provisioning and configuration of infrastructure resources. Provide guidance on the best use of specific tools or technologies to achieve desired results. Create documentation for infrastructure design and deployment procedures. Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, Scikit-learn, etc. Lead and manage AI/ML teams and projects from ideation to delivery and evaluation. Apply expertise in various AI/ML techniques, including deep learning, NLP, computer vision, recommender systems, reinforcement learning, and large language models. Proficiency in Python, R, or other programming languages for data analysis and AI/ML development. Communicate complex AI/ML concepts and results to technical and non-technical audiences effectively. Required Qualifications: A bachelor’s/master degree in computer science, engineering, mathematics, statistics, or a related discipline 12+ years of experience in Software Engineering, Data Science, or Analytics with at least 8 years of experience in AI/ML engineering or related fields Experience with cloud platforms and services, such as AWS, Azure, GCP, etc. Experience in developing solutions in the NLP space and relevant projects. Proficiency in multiple machine learning and AI techniques such as supervised, unsupervised, reinforcement learning, deep learning, and NLP. Understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering. . Demonstrated experience in leading and managing AI/ML teams and projects, from ideation to delivery and evaluation Familiarity with both open-source and OpenAI LLMs and RAG architecture. Proficient in Python and one of PySpark or Scala. Familiarity with python tools for data processing Ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML) Knowledge of NLP literature, thrust areas, conference venues, and code repositories. Familiarity with UI tools like Streamlit, Flask, FAST APIs, Rest APIs, Docker containers. Proficiency in libraries such as Hugging Face and OpenAI API. Experience with Azure development environments Proven excellent communication, presentation, and interpersonal skills, with the ability to explain complex AI/ML concepts and results to technical and non-technical audiences Solid analytical, problem-solving, and decision-making skills, with the ability to balance innovation and pragmatism A passion for learning and staying updated with the latest AI/ML trends and research

We are seeking a forward-thinking AI Architect to design, lead, and scale enterprise-grade AI systems and solutions across domains. This role demands deep expertise in machine learning, generative AI, data engineering, cloud-native architecture, and orchestration frameworks. You will collaborate with cross-functional teams to translate business requirements into intelligent, production-ready AI solutions. Key Responsibilities: Architecture & Strategy Design end-to-end AI architectures that include data pipelines, model development, MLOps, and inference serving. Create scalable, reusable, and modular AI components for different use cases (vision, NLP, time series, etc.). Drive architecture decisions across AI solutions, including multi-modal models, LLMs, and agentic workflows. Ensure interoperability of AI systems across cloud (AWS/GCP/Azure), edge, and hybrid environments. Technical Leadership Guide teams in selecting appropriate models (traditional ML, deep learning, transformers, etc.) and technologies. Lead architectural reviews and ensure compliance with security, performance, and governance policies. Mentor engineering and data science teams in best practices for AI/ML, GenAI, and MLOps. Model Lifecycle & Engineering Oversee implementation of model lifecycle using CI/CD for ML (MLOps) and/or LLMOps workflows. Define architecture for Retrieval Augmented Generation (RAG), vector databases, embeddings, prompt engineering, etc. Design pipelines for fine-tuning, evaluation, monitoring, and retraining of models. Data & Infrastructure Collaborate with data engineers to ensure data quality, feature pipelines, and scalable data stores. Architect systems for synthetic data generation, augmentation, and real-time streaming inputs. Define solutions leveraging data lakes, data warehouses, and graph databases. Client Engagement / Product Integration Interface with business/product stakeholders to align AI strategy with KPIs. Collaborate with DevOps teams to integrate models into products via APIs/microservices. Required Skills & Experience: Core Skills Strong foundation in AI/ML/DL (Scikit-learn, TensorFlow, PyTorch, Transformers, Langchain, etc.) Advanced knowledge of Generative AI (LLMs, diffusion models, multimodal models, etc.) Proficiency in cloud-native architectures (AWS/GCP/Azure) and containerization (Docker, Kubernetes) Experience with orchestration frameworks (Airflow, Ray, LangGraph, or similar) Familiarity with vector databases (Weaviate, Pinecone, FAISS), LLMOps platforms, and RAG design Architecture & Programming Solid experience in architectural patterns (microservices, event-driven, serverless) Proficient in Python and optionally Java/Go Knowledge of APIs (REST, GraphQL), streaming (Kafka), and observability tooling (Prometheus, ELK, Grafana) Tools & Platforms ML lifecycle tools: MLflow, Kubeflow, Vertex AI, Sagemaker, Hugging Face, etc. Prompt orchestration tools: LangChain, CrewAI, Semantic Kernel, DSPy (nice to have) Knowledge of security, privacy, and compliance (GDPR, SOC2, HIPAA, etc.)

Bloomreach is building the world’s premier agentic platform for personalization .We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey. We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses. We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey. We're designing the future of autonomous marketing, taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do. And we're building all of that on the intelligence of a single AI engine — Loomi AI — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora. We are seeking a Senior AI Engineer to join our dynamic team. In this role, you will be instrumental in building data-driven ML/AI algorithms that enhance our search and recommendation systems. Your primary focus will be on data engineering, analysis, transformations, model training, and serving, ensuring practical and scalable applications of machine learning within our products. This position emphasizes productization and the implementation of ML/AI solutions over pure data science and research, making it ideal for professionals thriving in the fast-paced generative AI era. Key Responsibilities Data Engineering & Analysis Slice and dice analytics data to formulate hypotheses and generate ideas to improve search and recommendation performance. Perform comprehensive data transformations to prepare datasets for model training and evaluation. Build and maintain data pipelines using tools like Airflow, Kubeflow, and MLflow to support ML/AI workflows. Model Development & Deployment Design, develop, and enhance machine learning and AI models tailored to product discovery and search functionalities. Conduct feature engineering to extract meaningful insights from historical data, search queries, product catalogs, and images. Collaborate with Data Engineers to integrate and scale ML components to production-level systems capable of handling large-scale data. Ensure seamless deployment of models, maintaining high availability and performance in cloud environments. Algorithm Implementation & Optimization Dive deep into algorithm applicability, performing impact analysis to ensure models meet performance and business objectives. Optimize and build new algorithms to address various challenges in product discovery and search. Productization of ML/AI Solutions Translate data-driven insights and models into actionable product features that enhance user experience. Work closely with Data Science, Product and Engineering teams to implement practical ML/AI applications that drive business outcomes. Continuous Learning & Improvement Stay abreast of the latest advancements in ML/AI, particularly in generative AI and large language models (LLMs). Continuously refine and improve existing models and workflows based on new research and industry trends. Qualifications Educational Background BS/MS degree in Computer Science, Engineering, Mathematics, or a related discipline with a strong mathematical foundation. Experience 5-8 years of experience building ML-driven, fast, and scalable ML/AI algorithms in a corporate or startup environment. Technical Skills Proficient in Python with excellent programming skills. Strong understanding of machine learning and natural language processing technologies, including classification, information retrieval, clustering, knowledge graphs, semi-supervised learning, and ranking. Experience with deep learning frameworks such as PyTorch, Keras, or TensorFlow. Proficient in SQL and experience with data warehouses like Redshift or BigQuery. Experience with big data technologies such as Hadoop, Spark, Kafka, and data lakes for large-scale processing. Strong understanding of data structures, algorithms, and system design for building highly available, high-performance systems. Experience with workflow orchestration and ML pipeline tools such as Airflow, Kubeflow, and MLflow. Specialized Knowledge Strong awareness of recent trends in Generative AI and Large Language Models (LLMs). Experience working with the GenAI stack is highly desirable. Soft Skills Excellent problem-solving and analytical skills with the ability to adapt to new ML technologies. Effective communication skills in English, both verbal and written. Ability to work collaboratively in a fast-paced, agile environment. More things you'll like about Bloomreach: Culture: A great deal of freedom and trust. At Bloomreach we don’t clock in and out, and we have neither corporate rules nor long approval processes. This freedom goes hand in hand with responsibility. We are interested in results from day one. We have defined our 5 values and the 10 underlying key behaviors that we strongly believe in. We can only succeed if everyone lives these behaviors day to day. We've embedded them in our processes like recruitment, onboarding, feedback, personal development, performance review and internal communication. We believe in flexible working hours to accommodate your working style. We work virtual-first with several Bloomreach Hubs available across three continents. We organize company events to experience the global spirit of the company and get excited about what's ahead. We encourage and support our employees to engage in volunteering activities - every Bloomreacher can take 5 paid days off to volunteer*. The Bloomreach Glassdoor page elaborates on our stellar 4.4/5 rating. The Bloomreach Comparably page Culture score is even higher at 4.9/5 Personal Development: We have a People Development Program -- participating in personal development workshops on various topics run by experts from inside the company. We are continuously developing & updating competency maps for select functions. Our resident communication coach Ivo Večeřa is available to help navigate work-related communications & decision-making challenges.* Our managers are strongly encouraged to participate in the Leader Development Program to develop in the areas we consider essential for any leader. The program includes regular comprehensive feedback, consultations with a coach and follow-up check-ins. Bloomreachers utilize the $1,500 professional education budget on an annual basis to purchase education products (books, courses, certifications, etc.)* Well-being: The Employee Assistance Program -- with counselors -- is available for non-work-related challenges.* Subscription to Calm - sleep and meditation app.* We organize ‘DisConnect’ days where Bloomreachers globally enjoy one additional day off each quarter, allowing us to unwind together and focus on activities away from the screen with our loved ones. We facilitate sports, yoga, and meditation opportunities for each other. Extended parental leave up to 26 calendar weeks for Primary Caregivers.* Compensation: Restricted Stock Units or Stock Options are granted depending on a team member’s role, seniority, and location.* Everyone gets to participate in the company's success through the company performance bonus.* We offer an employee referral bonus of up to $3,000 paid out immediately after the new hire starts. We reward & celebrate work anniversaries -- Bloomversaries!* (*Subject to employment type. Interns are exempt from marked benefits, usually for the first 6 months.) Excited? Join us and transform the future of commerce experiences! If this position doesn't suit you, but you know someone who might be a great fit, share it - we will be very grateful! Any unsolicited resumes/candidate profiles submitted through our website or to personal email accounts of employees of Bloomreach are considered property of Bloomreach and are not subject to payment of agency fees.

Job Title: AI/ML engineer Location: Gurgaon Hybrid Experience: 4–9 Years Job Type: [Full-time ] Job Summary: We are seeking a highly skilled and motivated AI/ML Engineer with strong AWS Cloud experience to join our data science and engineering team. The ideal candidate will design, build, and deploy scalable machine learning models and solutions while leveraging AWS services to manage infrastructure and model workflows. Key Responsibilities: Design, develop, and deploy machine learning models for predictive analytics, classification, NLP, or computer vision tasks. Use AWS services like SageMaker, S3, Lambda, Glue, EC2, EKS, and Step Functions for ML workflows and deployments. Preprocess and analyze large datasets for training and inference. Build scalable data pipelines and automate model training and evaluation. Collaborate with data engineers, scientists, and DevOps teams to productionize models. Optimize models for performance, interpretability, and scalability. Implement MLOps best practices (versioning, monitoring, model retraining pipelines). Conduct A/B testing and model performance tuning. Key Skills and Qualifications: Technical Skills: Strong proficiency in Python (including pandas, NumPy, Scikit-learn, etc.) Solid understanding of ML algorithms (regression, classification, clustering, deep learning) Experience with TensorFlow, PyTorch, or Keras Hands-on experience with AWS cloud services : SageMaker , S3 , Glue , Lambda , Step Functions , CloudWatch , IAM , etc. Experience with MLOps tools : MLflow, Docker, Git, CI/CD pipelines Knowledge of data pipeline frameworks (Airflow, AWS Glue, etc.) Familiarity with SQL and data wrangling in distributed environments (e.g., Spark) Nice to Have: Experience with NLP, LLMs, or Computer Vision Exposure to Big Data technologies (Kafka, Hadoop, etc.) Familiarity with API development using Flask or FastAPI Knowledge of Kubernetes for model container orchestration Educational Qualifications: Bachelor’s or Master’s in Computer Science, Data Science, Statistics, or related field.

Highly skilled Senior Machine Learning Engineer with expertise in Deep Learning, Large Language Models (LLMs), and MLOps/LLMOps to design, optimize, and deploy cutting-edge AI solutions. The ideal candidate will have hands-on experience in developing and scaling deep learning models, fine-tuning LLMs/ (e.g., GPT, Llama), and implementing robust deployment pipelines for production environments. Responsibilities Model Development & Fine-Tuning: - Design, train, fine-tune and optimize deep learning models (CNNs, RNNs, Transformers) for NLP, computer vision, or multimodal applications. - Fine-tune and adapt Large Language Models (LLMs) for domain-specific tasks (e.g., text generation, summarization, semantic similarity). - Experiment with RLHF (Reinforcement Learning from Human Feedback) and other alignment techniques. Deployment & Scalability (MLOps/LLMOps): - Build and maintain end-to-end ML pipelines for training, evaluation, and deployment. - Deploy LLMs and deep learning models in production environments using frameworks like FastAPI, vLLM, or TensorRT. - Optimize models for low-latency, high-throughput inference (eg., quantization, distillation, etc.). - Implement CI/CD workflows for ML systems using tools like MLflow, Kubeflow. Monitoring & Optimization: - Set up logging, monitoring, and alerting for model performance (drift, latency, accuracy). - Work with DevOps teams to ensure scalability, security, and cost-efficiency of deployed models. Required Skills & Qualifications: - 5-7 years of hands-on experience in Deep Learning, NLP, and LLMs. - Strong proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers, and LLM frameworks. - Experience with model deployment tools (Docker, Kubernetes, FastAPI). - Knowledge of MLOps/LLMOps best practices (model versioning, A/B testing, canary deployments). - Familiarity with cloud platforms (AWS, GCP, Azure). Preferred Qualifications: - Contributions to open-source LLM projects.

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.

Technology Gurgaon, India Publicis Re:Sources India Intermediate On-Site 7/7/2025 115065 Company description Re:Sources is the backbone of Publicis Groupe, the world's third-largest communications group. Formed in 1998 as a small team to service a few Publicis Groupe firms, Re:Sources has grown to 5,000+ people servicing a global network of prestigious advertising, public relations, media, healthcare and digital marketing agencies. We provide technology solutions and business services including finance, accounting, legal, benefits, procurement, tax, real estate, treasury and risk management to help Publicis Groupe agencies do what they do best: create and innovate for their clients. In addition to providing essential, everyday services to our agencies, Re:Sources develops and implements platforms, applications and tools to enhance productivity, encourage collaboration and enable professional and personal development. We continually transform to keep pace with our ever-changing communications industry and thrive on a spirit of innovation felt around the globe. With our support, Publicis Groupe agencies continue to create and deliver award-winning campaigns for their clients. Overview Title GEN AI and Machine Learning Engineer Skills (must have) Bachelor's or master’s degree in Computer Science, Data Science, Engineering, or a related field. Experience on Agentic AI/ Frameworks Strong programming skills in languages such as Python, SQL etc. Build analytical approach based on business requirements, then develop, train, and deploy machine learning models and AI algorithms Exposure to GEN AI models such as OpenAI, Google Gemini, Runway ML etc. Experience in developing and deploying AI/ML and deep learning solutions with libraries and frameworks, such as TensorFlow, PyTorch, Scikit-learn, OpenCV and/or Keras. Knowledge of math, probability, and statistics. Familiarity with a variety of Machine Learning, NLP, and deep learning algorithms. Exposure in developing API using Flask/Django. Good experience in cloud infrastructure such as AWS, Azure or GCP Exposure to Gen AI, Vector DB/Embeddings, LLM (Large language Model) Skills (good to have) Experience with MLOps: MLFlow, Kubeflow, CI/CD Pipeline etc. Good to have experience in Docker, Kubernetes etc Exposure in HTML, CSS, Javascript/JQuery, Node.js, Angular/React Experience in Flask/Django is a bonus Responsibilities Collaborate with software engineers, business stake holders and/or domain experts to translate business requirements into product features, tools, projects, AI/ML, NLP/NLU and deep learning solutions. Develop, implement, and deploy AI/ML solutions. Preprocess and analyze large datasets to identify patterns, trends, and insights. Evaluate, validate, and optimize AI/ML models to ensure their accuracy, efficiency, and generalizability. Deploy applications and AI/ML model into cloud environment such as AWS/Azure/GCP etc. Monitor and maintain the performance of AI/ML models in production environments, identifying opportunities for improvement and updating models as needed. Document AI/ML model development processes, results, and lessons learned to facilitate knowledge sharing and continuous improvement.

We are looking for experienced data scientists, who have the aspirations and appetite for working in a start-up environment, and with relevant industry experience to make a significant contribution to our platform and solutions. Primary focus would be to apply machine learning techniques for data extraction from documents from variety of formats including scans and handwritten documents. Responsibilities: Develop a learning model for high accuracy extraction and validation of documents, e.g. in mortgage industry Work with state-of-the-art language modelling approaches such as transformer-based architectures while integrating capabilities across NLP, computer vision, and machine learning to build robust multi-modal AI solutions Interact with clients and other team members to understand client-specific requirements of the platform Contribute to platform development team and deliver platform releases in a timely manner • Liaise with multiple stakeholders and coordinate with our onshore and offshore entities • Evaluate and compile the required training datasets from internal and public sources and contribute to the data pre-processing phase. Expected and Desired Skills Either of the following Deep learning frameworks – PyTorch (preferred) or Tensorflow • Good understanding in designing, developing, and optimizing Large Language Models (LLMs), with hands-on experience in leveraging cutting-edge advancements in NLP and generative AI Skilled in customizing LLMs for domain-specific applications through advanced fine-tuning, prompt engineering, and optimization strategies such as LoRA, quantization, and distillation. • Knowledge of model versioning, serving, and monitoring using tools like MLflow, FastAPI, Docker, vLLM. Python used for analytics applications including data pre-processing, EDA, statistical analysis, machine learning model performance evaluation and benchmarking Good scripting and programming skills to integrate with other external applications • Good interpersonal skills and the ability to communicate and explain models • Ability to work in unfamiliar business areas and to use your skills to create solutions • Ability to both work in and lead a team and to deliver and accept peer review • Flexible approach to working environment and hours. Experience Between 4-6 years of relevant experience Hands-on experience with o Python and/or R o Machine Learning o Deep Learning (desirable) End to End development of a Deep Learning based model covering model selection, data preparation, training, hyper-parameter optimization, evaluation, and performance reporting. Proven experience working in both smaller and larger organisations having multicultural exposure Domain and industry experience by serving customers in one or more of these industries - Financial Services, Professional Services, other Consumer Industries Education Background: A Bachelor’s degree in the fields of study such as Computer Science, Mathematics, Statistics, and Data Science with strong programming content from a leading institute An advanced degree such as a Master's or PhD is an advantage Job Type: Full-time Pay: ₹1,000,000.00 - ₹2,000,000.00 per year Schedule: Day shift Fixed shift Work Location: In person

Required Skills We are looking for an experienced AI Engineer to join our team. The ideal candidate will have a strong background in designing, deploying, and maintaining advanced AI/ML models with expertise in Natural Language Processing (NLP), Computer Vision, and architectures like Transformers and Diffusion Models. You will play a key role in developing AI-powered solutions, optimizing performance, and deploying and managing models in production environments. Key Responsibilities 1. AI Model Development and Optimization: Design, train, and fine-tune AI models for NLP, Computer Vision, and other domains using frameworks like TensorFlow and PyTorch. Work on advanced architectures, including Transformer-based models (e.g., BERT, GPT, T5) for NLP tasks and CNN-based models (e.g., YOLO, VGG, ResNet) for Computer Vision applications. Utilize techniques like PEFT (Parameter-Efficient Fine-Tuning) and SFT (Supervised Fine-Tuning) to optimize models for specific tasks. Build and train RLHF (Reinforcement Learning with Human Feedback) and RL-based models to align AI behavior with real-world objectives., Explore multimodal AI solutions combining text, vision, and audio using generative deep learning architectures. 2. Natural Language Processing (NLP): Develop and deploy NLP solutions, including language models, text generation, sentiment analysis, and text-to-speech systems. Leverage advanced Transformer architectures (e.g., BERT, GPT, T5) for NLP tasks. 3. AI Model Deployment and Frameworks: Deploy AI models using frameworks like VLLM, Docker, and MLFlow in production-grade environments. Create robust data pipelines for training, testing, and inference workflows. Implement CI/CD pipelines for seamless integration and deployment of AI solutions. 4. Production Environment Management: Deploy, monitor, and manage AI models in production, ensuring performance, reliability, and scalability. Set up monitoring systems using Prometheus to track metrics like latency, throughput, and model drift. 5. Data Engineering and Pipelines: Design and implement efficient data pipelines for preprocessing, cleaning, and transformation of large datasets. Integrate with cloud-based data storage and retrieval systems for seamless AI workflows. 6. Performance Monitoring and Optimization: Optimize AI model performance through hyperparameter tuning and algorithmic improvements. Monitor performance using tools like Prometheus, tracking key metrics (e.g., latency, accuracy, model drift, error rates etc.) 7. Solution Design and Architecture: Collaborate with cross-functional teams to understand business requirements and translate them into scalable, efficient AI/ML solutions. Design end-to-end AI systems, including data pipelines, model training workflows, and deployment architectures, ensuring alignment with business objectives and technical constraints. Conduct feasibility studies and proof-of-concepts (PoCs) for emerging technologies to evaluate their applicability to specific use cases. 8. Stakeholder Engagement: Act as the technical point of contact for AI/ML projects, managing expectations and aligning deliverables with timelines. Participate in workshops, demos, and client discussions to showcase AI capabilities and align solutions with client needs. Technical Skills Proficient in Python , with strong knowledge of libraries like NumPy, Pandas, SciPy, and Matplotlib for data manipulation and visualization. Expertise in TensorFlow, PyTorch, Scikit-learn, and Keras for building, training, and optimizing machine learning and deep learning models. Hands-on experience with Transformer libraries like Hugging Face Transformers, OpenAI APIs, and LangChain for NLP tasks. Practical knowledge of CNN architectures (e.g., YOLO, ResNet, VGG) and Vision Transformers (ViT) for Computer Vision applications. Proficiency in developing and deploying Diffusion Models like Stable Diffusion, SDX, and other generative AI frameworks. Experience with RLHF (Reinforcement Learning with Human Feedback) and reinforcement learning algorithms for optimizing AI behaviors. Proficiency with Docker and Kubernetes for containerization and orchestration of AI workflows. Hands-on experience with MLOps tools such as MLFlow for model tracking and CI/CD integration in AI pipelines. Expertise in setting up monitoring tools like Prometheus and Grafana to track model performance, latency, throughput, and drift. Knowledge of performance optimization techniques, such as quantization, pruning, and knowledge distillation, to improve model efficiency. Experience in building data pipelines for preprocessing, cleaning, and transforming large datasets using tools like Apache Airflow, Luigi Familiarity with cloud-based storage systems (e.g., AWS S3, Google BigQuery) for efficient data handling in AI workflows. Strong understanding of cloud platforms (AWS, GCP, Azure) for deploying and scaling AI solutions. Knowledge of advanced search technologies such as Elasticsearch for indexing and querying large datasets. Familiarity with edge deployment frameworks and optimization for resource-constrained environments Qualifications · Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field. Experience: 2.5 to 5 yrs Location: Trivandrum Job Type: Full-time Pay: ₹500,000.00 - ₹1,100,000.00 per year Benefits: Health insurance Provident Fund Location Type: In-person Schedule: Day shift Work Location: In person

Experience Required: 3-5 years of hands-on experience in full-stack development, system design, and supporting AI/ML data-driven solutions in a production environment. Key Responsibilities Implementing Technical Designs: Collaborate with architects and senior stakeholders to understand high-level designs and break them down into detailed engineering tasks. Implement system modules and ensure alignment with architectural direction. Cross-Functional Collaboration: Work closely with software developers, data scientists, and UI/UX teams to translate system requirements into working code. Clearly communicate technical concepts and implementation plans to internal teams. Stakeholder Support: Participate in discussions with product and client teams to gather requirements. Provide regular updates on development progress and raise flags early to manage expectations. System Development & Integration: Develop, integrate, and maintain components of AI/ML platforms and data-driven applications. Contribute to scalable, secure, and efficient system components based on guidance from architectural leads. Issue Resolution: Identify and debug system-level issues, including deployment and performance challenges. Proactively collaborate with DevOps and QA to ensure resolution. Quality Assurance & Security Compliance: Ensure that implementations meet coding standards, performance benchmarks, and security requirements. Perform unit and integration testing to uphold quality standards. Agile Execution: Break features into technical tasks, estimate efforts, and deliver components in sprints. Participate in sprint planning, reviews, and retrospectives with a focus on delivering value. Tool & Framework Proficiency: Use modern tools and frameworks in your daily workflow, including AI/ML libraries, backend APIs, front-end frameworks, databases, and cloud services, contributing to robust, maintainable, and scalable systems. Continuous Learning & Contribution: Keep up with evolving tech stacks and suggest optimizations or refactoring opportunities. Bring learnings from the industry into internal knowledge-sharing sessions. Proficiency in using AI-copilots for Coding: Adaptation to emerging tools and knowledge of prompt engineering to effectively use AI for day-to-day coding needs. Technical Skills Hands-on experience with Python-based AI/ML development using libraries such as TensorFlow, PyTorch, scikit-learn, or Keras. Hands-on exposure to self-hosted or managed LLMs, supporting integration and fine-tuning workflows as per system needs while following architectural blueprints. Practical implementation of NLP/CV modules using tools like SpaCy, NLTK, Hugging Face Transformers, and OpenCV, contributing to feature extraction, preprocessing, and inference pipelines. Strong backend experience using Django, Flask, or Node.js, and API development (REST or GraphQL). Front-end development experience with React, Angular, or Vue.js, with a working understanding of responsive design and state management. Development and optimization of data storage solutions, using SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra), with hands-on experience configuring indexes, optimizing queries, and using caching tools like Redis and Memcached. Working knowledge of microservices and serverless patterns, participating in building modular services, integrating event-driven systems, and following best practices shared by architectural leads. Application of design patterns (e.g., Factory, Singleton, Observer) during implementation to ensure code reusability, scalability, and alignment with architectural standards. Exposure to big data tools like Apache Spark, and Kafka for processing datasets. Familiarity with ETL workflows and cloud data warehouse, using tools such as Airflow, dbt, BigQuery, or Snowflake. Understanding of CI/CD, containerization (Docker), IaC (Terraform), and cloud platforms (AWS, GCP, or Azure). Implementation of cloud security guidelines, including setting up IAM roles, configuring TLS/SSL, and working within secure VPC setups, with support from cloud architects. Exposure to MLOps practices, model versioning, and deployment pipelines using MLflow, FastAPI, or AWS SageMaker. Configuration and management of cloud services such as AWS EC2, RDS, S3, Load Balancers, and WAF, supporting scalable infrastructure deployment and reliability engineering efforts. Personal Attributes Proactive Execution and Communication: Able to take architectural direction and implement it independently with minimal rework with regular communication with stakeholders Collaboration: Comfortable working across disciplines with designers, data engineers, and QA teams. Responsibility: Owns code quality and reliability, especially in production systems. Problem Solver: Demonstrated ability to debug complex systems and contribute to solutioning. Key: Python, Django, Django ORM, HTML, CSS, Bootstrap, JavaScript, jQuery, Multi-threading, Multi-processing, Database Design, Database Administration, Cloud Infrastructure, Data Science, self-hosted LLMs Qualifications Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, or a related field. Relevant certifications in cloud or machine learning are a plus. Package: 6-11 LPA Job Types: Full-time, Permanent Pay: ₹600,000.00 - ₹800,000.00 per year Benefits: Health insurance Life insurance Provident Fund Schedule: Day shift Monday to Friday

Line of Service Advisory Industry/Sector GPS X-Sector Specialism Operations Management Level Senior Associate Job Description & Summary At PwC, our people in software and product innovation focus on developing cutting-edge software solutions and driving product innovation to meet the evolving needs of clients. These individuals combine technical experience with creative thinking to deliver innovative software products and solutions. In business analysis at PwC, you will focus on analysing and interpreting data to provide strategic insights and recommendations for improving business performance. Your work will involve strong analytical skills and the ability to effectively communicate findings to stakeholders. *Why PWC At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more about us . At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm’s growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. Job Description & Summary: At PwC, our purpose is to build trust in society and solve important problems. We’re a network of firms in 157 countries with more than 300,000 people who are committed to delivering quality in Assurance, Advisory and Tax services. Within Advisory, PwC has a large team that focus on transformation in Government through Digital inclusion. The open position is for a candidate who desires to work with government clients and bring about a change in society. A successful candidate will be expected to work pro-actively and effectively on multiple client engagements over the period of time and take ownership of the entire project delivery he/she entrusted with. Responsibilities: · Lead the design and implementation of AI/ML models, particularly in the areas of Generative AI and advanced data analytics · Develop and fine-tune large language models (LLMs) and transformer-based architectures for specific use cases · Collaborate with data engineers, product owners and business stakeholders to translate requirements into intelligent solutions · Deploy ML models in production using MLOps practices, ensuring scalability and performance · Drive experimentation with cutting-edge Gen AI techniques (e.g., text generation, summarization, image synthesis) · Conduct data exploration, feature engineering and statistical modeling to support various business needs · Mentor junior team members and guide them in model development and evaluation best practices · Stay up to date with the latest research and industry trends in AI, ML and Gen AI · Document methodologies, models and workflows for knowledge sharing and reuse Mandatory skill sets: · 4+ years of experience in AI/ML and data science, with proven experience in Generative AI · Hands-on expertise with Python and relevant ML/AI libraries (e.g., PyTorch, TensorFlow, Hugging Face, Scikit-learn) · Strong understanding of LLMs (e.g., GPT, BERT, T5), transformers and prompt engineering · Experience with NLP techniques such as text classification, summarization, entity recognition and conversational AI · Ability to build and evaluate supervised and unsupervised learning models · Proficient in data wrangling, exploratory data analysis and statistical techniques · Familiarity with model deployment tools and platforms (Docker, FastAPI, MLflow, AWS/GCP/Azure ML services) · Excellent problem-solving, analytical thinking and communication skills Preferred skill sets : · Experience fine-tuning open-source LLMs using domain-specific data · Exposure to reinforcement learning (RLHF), diffusion models or multimodal AI · Familiarity with vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG) architectures · Experience with ML pipelines and automation (CI/CD for ML, Kubeflow, Airflow) · Background in conversational AI, chatbots or virtual assistants · Knowledge of data privacy, ethical AI and explainable AI principles · Publications, Kaggle participation or open-source contributions in the AI/ML space Years of experience required: 4+ years Education qualification : · Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Statistics or a related field Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Bachelor Degree, Master Degree Degrees/Field of Study preferred: Certifications (if blank, certifications not specified) Required Skills Artificial Intelligence Markup Language, PyTorch, Scikit-Learn, Tensorflow Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Analytical Thinking, Business Administration, Business Analysis, Business Case Development, Business Data Analytics, Business Process Analysis, Business Process Modeling, Business Process Re-Engineering (BPR), Business Requirements Analysis, Business Systems, Communication, Competitive Analysis, Creativity, Embracing Change, Emotional Regulation, Empathy, Feasibility Studies, Functional Specification, Inclusion, Intellectual Curiosity, IT Project Lifecycle, Learning Agility {+ 19 more} Desired Languages (If blank, desired languages not specified) Travel Requirements Not Specified Available for Work Visa Sponsorship? No Government Clearance Required? No Job Posting End Date

About us: Where elite tech talent meets world-class opportunities! At Xenon7, we work with leading enterprises and innovative startups on exciting, cutting-edge projects that leverage the latest technologies across various domains of IT including Data, Web, Infrastructure, AI, and many others. Our expertise in IT solutions development and on-demand resources allows us to partner with clients on transformative initiatives, driving innovation and business growth. Whether it's empowering global organizations or collaborating with trailblazing startups, we are committed to delivering advanced, impactful solutions that meet today’s most complex challenges. We are building a community of top-tier experts and we’re opening the doors to an exclusive group of exceptional AI & ML Professionals ready to solve real-world problems and shape the future of intelligent systems. Structured Onboarding Process We ensure every member is aligned and empowered: Screening – We review your application and experience in Data & AI, ML engineering, and solution delivery Technical Assessment – 2-step technical assessment process that includes an interactive problem-solving test, and a verbal interview about your skills and experience Matching you to Opportunity – We explore how your skills align with ongoing projects and innovation tracks Who We're Looking For We’re looking for a Senior MLOps Engineer with deep expertise in the Databricks ecosystem to help us build and scale reliable, secure, and automated ML platforms across enterprise environments. You’ll work closely with data scientists, ML engineers, DevOps teams, and cloud architects to implement and maintain production-grade machine learning infrastructure using best practices in MLOps, CI/CD, and cloud-native services. This is a hands-on technical leadership role ideal for engineers who can work across the entire ML lifecycle—from experiment tracking to scalable deployment—while championing automation, governance, and performance. If you're driven by curiosity and eager to influence how AI shapes the future, this is your platform. Requirements 6+ years of professional experience in DevOps, DataOps, or MLOps roles 3+ years hands-on with Databricks , including Delta Lake, MLflow, and cluster/workflow administration Strong experience in CI/CD , infrastructure as code (Terraform, GitOps), and Python-based automation Solid understanding of ML lifecycle management , experiment tracking, model registries, and automated deployment pipelines Deep knowledge of AWS (EKS, IAM, Lambda, CloudFormation or Terraform) and/or Azure (ADLS, Azure DevOps, ACR) Experience working with containerized environments, including Kubernetes and Helm Familiarity with data governance and access control frameworks like Unity Catalog Strong scripting and programming skills in Python, Shell, and YAML/JSON Benefits At Xenon7, we're not just building AI systems—we're building a community of talent with the mindset to lead, collaborate, and innovate together. Ecosystem of Opportunity: You'll be part of a growing network where client engagements, thought leadership, research collaborations, and mentorship paths are interconnected. Whether you're building solutions or nurturing the next generation of talent, this is a place to scale your influence. Collaborative Environment: Our culture thrives on openness, continuous learning, and engineering excellence. You'll work alongside seasoned practitioners who value smart execution and shared growth. Flexible & Impact-Driven Work: Whether you're contributing from a client project, innovation sprint, or open-source initiative, we focus on outcomes—not hours. Autonomy, ownership, and curiosity are encouraged here. Talent-Led Innovation: We believe communities are strongest when built around real practitioners. Our Innovation Community isn’t just a knowledge-sharing forum—it’s a launchpad for members to lead new projects, co-develop tools, and shape the direction of AI itself.

Job Summary: We are looking for a passionate and skilled AI/ML Developer with a minimum of 2 years of experience to join our team. The ideal candidate will be responsible for developing machine learning models, implementing AI solutions, and collaborating with cross-functional teams to integrate these systems into production environments. Key Responsibilities: Design, develop, and deploy machine learning models and AI systems. Collect, preprocess, and analyze large datasets from diverse sources. Optimize and fine-tune models for performance and scalability. Work with engineering teams to integrate ML models into production-ready applications. Monitor and maintain deployed models, and retrain as needed. Stay current with the latest research and trends in AI and machine learning. Document processes, experiments, and outcomes for transparency and reproducibility. Required Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Minimum 2 years of hands-on experience in AI/ML development. Proficient in Python and libraries such as Scikit-learn, TensorFlow, PyTorch, or Keras. Strong understanding of machine learning algorithms, neural networks, and data structures. Experience with data processing tools (Pandas, NumPy), and model deployment frameworks (e.g., Flask, FastAPI, Docker). Familiarity with cloud platforms like AWS, GCP, or Azure. Knowledge of software development best practices (version control, testing, CI/CD). Preferred Qualifications: Experience with NLP, computer vision, or reinforcement learning. Knowledge of MLOps and model monitoring tools (MLflow, Kubeflow). Contribution to open-source projects or published ML research. Exposure to large-scale distributed systems or big data tools (Spark, Hadoop). Soft Skills: Strong problem-solving skills and analytical thinking. Excellent communication and team collaboration abilities. Self-motivated and eager to learn and implement new technologies. What We Offer: Competitive salary and performance-based bonuses. Flexible working hours and remote work options. Opportunity to work on cutting-edge AI/ML projects. Career development support and training opportunities. Collaborative, inclusive, and innovation-driven work culture. Job Types: Full-time, Permanent Pay: ₹13,671.07 - ₹85,229.87 per month Benefits: Paid sick time Paid time off Location Type: In-person Schedule: Day shift Fixed shift Monday to Friday Work Location: In person Speak with the employer +91 9016790313

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

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose – the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Assistant Vice President, Databricks Squad Delivery lead The Databricks Delivery Lead will oversee the end-to-end delivery of Databricks-based solutions for clients, ensuring the successful implementation, optimization, and scaling of big data and analytics solutions. This role will drive the adoption of Databricks as the preferred platform for data engineering and analytics, while managing a cross-functional team of data engineers and developers.. Responsibilities Lead and manage Databricks-based project delivery, ensuring that all solutions are designed, developed, and implemented according to client requirements, best practices, and industry standards. Act as the subject matter expert (SME) on Databricks, providing guidance to teams on architecture, implementation, and optimization. Collaborate with architects and engineers to design optimal solutions for data processing, analytics, and machine learning workloads. Serve as the primary point of contact for clients, ensuring alignment between business requirements and technical delivery. Maintain effective communication with stakeholders, providing regular updates on project status, risks, and achievements. Oversee the setup, deployment, and optimization of Databricks workspaces, clusters, and pipelines. Ensure that Databricks solutions are optimized for cost and performance, utilizing best practices for data storage, processing, and querying. Continuously evaluate the effectiveness of the Databricks platform and processes, suggesting improvements or new features that could enhance delivery efficiency and effectiveness. Drive innovation within the team, introducing new tools, technologies, and best practices to improve delivery quality.. Qualifications we seek in you! Minimum Qualifications / Skills Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s or MBA preferred). Relevant years in IT services with experience specifically in Databricks and cloud-based data engineering. Preferred Qualifications/ Skills Proven experience in leading end-to-end delivery of data engineering or analytics solutions on Databricks. Strong experience in cloud technologies (AWS, Azure, GCP), data pipelines, and big data tools. Hands-on experience with Databricks, Spark, Delta Lake, MLflow, and related technologies. Expertise in data engineering concepts, including ETL, data lakes, data warehousing, and distributed computing. Preferred Certifications: Databricks Certified Associate or Professional. Cloud certifications (AWS Certified Solutions Architect, Azure Data Engineer, or equivalent). Certifications in data engineering, big data technologies, or project management (e.g., PMP, Scrum Master). Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn , X , YouTube , and Facebook . Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Location: Hyderabad Department: Advanced AI Research & Engineering Reports To: Chief Technology Officer / Head of AI Strategy Employment Type: Full-time | Leadership Track Executive Summary: We are looking for a visionary and deeply experienced Artificial Intelligence Specialist to lead the design, architecture, and deployment of next-generation AI systems that will redefine our digital future. This role is reserved for an AI leader with demonstrated expertise in designing scalable, production-grade AI ecosystems; a deep understanding of neural architectures; and a track record of solving real-world complex challenges through intelligent automation, generative models, and predictive intelligence. This is not a conventional role—you will architect the AI backbone of future enterprise intelligence systems. Core Responsibilities: Architect and develop mission-critical AI models across domains: predictive analytics, generative AI, NLP, computer vision, and autonomous decision systems. Lead AI research-to-production workflows—from experimental design, data strategy, and model optimization to real-world deployment at scale. Design and refine advanced neural architectures , including transformers, LLMs, graph neural networks, and reinforcement learning agents. Spearhead multi-modal AI solutions integrating vision, voice, text, and time-series data streams. Collaborate with engineering, product, and C-suite teams to translate strategic business objectives into deployable AI solutions with measurable ROI. Guide data governance, ethical AI practices , explainability, compliance, and AI fairness protocols. Mentor a team of data scientists and machine learning engineers to deliver high-impact, production-ready AI pipelines. Continuously evaluate emerging AI tools, frameworks, and hardware acceleration techniques to maintain technological leadership . Represent the organization at AI conferences, forums, and research partnerships . Required Expertise: 10+ years of deep, hands-on experience in Artificial Intelligence, Machine Learning, and Applied Data Science. Master's or Ph.D. in AI/ML, Computer Science, Mathematics, Physics, or a related field (Ph.D. strongly preferred). Expertise in Python , along with frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, ONNX, Scikit-learn . Demonstrated experience building and deploying LLMs, GANs, CNNs, RNNs, RL agents , and large-scale vector search systems. Deep knowledge of data engineering pipelines, model lifecycle management, and distributed computing . Advanced proficiency with MLOps, CI/CD for ML , containerization (Docker, Kubernetes), and versioned model deployment tools (MLflow, Kubeflow). Solid grounding in probability, statistics, optimization , and algorithmic design. Experience deploying AI on cloud infrastructure (AWS, GCP, Azure) and leveraging GPU/TPU environments. Preferred Edge (Not Mandatory but Advantageous): Experience working with Autonomous Systems, AI OS, Digital Twins , or AI-powered Operating Systems . Prior contributions to open-source AI libraries , patents, or published research in Tier-1 conferences (NeurIPS, ICML, CVPR, ACL). Domain specialization in healthcare AI, fintech AI, smart cities, or autonomous governance platforms . Hands-on experience with AI compliance frameworks (GDPR, HIPAA, model interpretability, and ethical AI) . What You’ll Get: Leadership opportunity in building core AI infrastructure for enterprise-scale and city-scale platforms. Access to state-of-the-art infrastructure , including AI supercomputing environments and high-volume data systems. Competitive salary package with equity options , bonuses, and leadership growth. Opportunity to shape the AI strategy of high-impact products reaching millions globally. Work culture that fosters innovation, autonomy, and research-driven engineering . Application & Interview Process: Please submit: Updated CV with detailed project accomplishments GitHub / Research portfolio Shortlisted candidates will be invited for: A technical deep-dive session Strategic AI system design challenge Panel interview with leadership and R&D teams This Role is Built For: AI pioneers who don’t just build models — they architect future intelligence ecosystems . If you live at the intersection of mathematics, machine learning, systems design, and innovation, we invite you to define the next generation of AI with us.

Job Title: AI Architect Location: On-site / Hyderabad, India Position Type: Full-Time About the Company: Transnational AI Private Limited is a next-generation AI-first company committed to building scalable, intelligent systems for digital marketplaces, insurance, employment, and healthcare sectors. We drive innovation through AI engineering, data science, and seamless platform integration powered by event-driven architectures. Role Summary: We are looking for a highly motivated AI Engineer with strong experience in Python, FastAPI, and event-driven microservice architecture. You will be instrumental in building intelligent, real-time systems that power scalable AI workflows across our platforms. This role combines deep technical engineering skills with a product-oriented mindset. Key Responsibilities: Architect and develop AI microservices using Python and FastAPI within an event-driven ecosystem. Implement and maintain asynchronous communication between services using message brokers like Kafka, RabbitMQ, or NATS. Convert AI/ML models into production-grade, containerized services integrated with streaming and event-processing pipelines. Design and document async REST APIs and event-based endpoints with comprehensive OpenAPI/Swagger documentation. Collaborate with AI researchers, product managers, and DevOps engineers to deploy scalable and secure services. Develop reusable libraries, automation scripts, and shared components for AI/ML pipelines. Maintain high standards for code quality, testability, and observability using unit tests, logging, and monitoring tools. Work within Agile teams to ship features iteratively with a focus on scalability, resilience, and fault tolerance. Required Skills and Experience: Proficiency in Python 3.x with a solid understanding of asynchronous programming (async/await). Hands-on experience with FastAPI; knowledge of Flask or Django is a plus. Experience building and integrating event-driven systems using Kafka, RabbitMQ, Redis Streams, or similar technologies. Strong knowledge of event-driven microservices, pub/sub models, and real-time data streaming architectures. Exposure to deploying AI/ML models using PyTorch, TensorFlow, or scikit-learn. Familiarity with containerization (Docker), orchestration (Kubernetes), and cloud platforms (AWS, GCP, Azure). Experience with unit testing frameworks such as PyTest, and observability tools like Prometheus, Grafana, or OpenTelemetry. Understanding of security principles including JWT, OAuth2, and API security best practices. Nice to Have Experience with MLOps pipelines and tools like MLflow, DVC, or Kubeflow. Familiarity with Protobuf, gRPC, and async I/O with WebSockets. Prior work in real-time analytics, recommendation systems, or workflow orchestration (e.g., Prefect, Airflow). Contributions to open-source projects or active GitHub/portfolio. Educational Background: Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related technical discipline. Why Join Transnational AI? Build production-grade AI infrastructure powering real-world applications. Collaborate with domain experts and top engineers across marketplaces, insurance, and Workforce platforms. Flexible, remote-friendly environment with a focus on innovation and ownership. Competitive compensation, bonuses, and continuous learning support. Work on high-impact projects that influence how people discover jobs, get insured, and access personalized digital services.

About Codewalla At Codewalla, we don’t just experiment with AI—we ship AI-native products that scale. Born in New York and growing across India, we partner with ambitious startups to build the next generation of AI-accelerated software. Our work is fast-paced, deeply technical, and relentlessly user-focused. From LLM-powered copilots to vector search-backed dashboards, we bring AI from concept to production—without losing sight of cost, latency, or reliability. We don’t just believe in smart code. We believe in delivering smart experiences. About the Role We’re hiring an AI Applications Developer with 6–8 years of engineering experience —including at least 1 year building and shipping LLM-powered features in production. Your mission: translate raw model capability into lean, reliable, and user-ready features. You’ll work on Model Context Protocol (MCP) servers, build agentic clients, architect RAG pipelines, and automate LLM evaluations to ensure every release delivers measurable value. If you thrive on rapid iteration, prompt experimentation, and seeing your code make it into users’ hands—we’d love to hear from you. What You’ll Work On Build MCP servers and agentic clients that handle user intent parsing, tool orchestration, and structured response generation Architect efficient RAG pipelines with chunk decay, latency budgeting, and cost-aware vector search Automate evaluation pipelines that test LLM outputs for relevance, accuracy, and coherence Work closely with DevOps to codify and deploy infrastructure using CDK or Terraform Set up observability dashboards for prompt performance, latency, and failure traceability Continuously refine prompts, embeddings, and model behavior based on user feedback and regression tests What Makes You a Great Fit 6–8 years of full-stack or backend development experience, with at least 1 year building AI-powered or LLM-based applications AI-native mindset: test fast, trace deeply, pause to reframe when needed Strong Python and TypeScript skills Experience with either AWS or GCP stacks, such as: AWS: Lambda, Bedrock, DynamoDB, OpenSearch Vector Search GCP: Cloud Functions, Vertex AI, Firestore, BigQuery, Vector Search Familiarity with LangChain, Bedrock SDK, and vector database schema design Understanding of prompt design, embeddings, and agentic workflows CI/CD fluency—GitHub Actions, containerized deployment, test-first habits Experience with LLM evaluation tools like Promptfoo, LangSmith, or Guardrails Bonus: Experience with MLflow, LaunchDarkly, Inferentia/GPU tuning Tools & Tech We Work With Languages: Python, TypeScript Frameworks: LangChain, FastAPI, Next.js Cloud: AWS (Bedrock, Lambda, DynamoDB, OpenSearch Vector Search) or GCP (Vertex AI, Cloud Functions, Firestore, BigQuery, Vector Search) Dev Tools: GitHub Copilot, Cursor Evaluation & Safety: Promptfoo, LangSmith, Guardrails DevOps: GitHub Actions, CDK or Terraform, Docker, Prometheus, Grafana Why Join Codewalla? Work at the forefront of AI-native product development Ship features that go from prototype to production, not just to playgrounds Collaborate with world-class teams building real-world tools for global users Influence everything—from prompt strategy to model integration and deployment pipelines Your code will shape actual user experience—not just a research slide deck Inclusion Matters We’re an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all team members. Ready to build the future with LLMs—without waiting for the future to catch up? Apply now and let’s build together.

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. Quality Assurance: Rigorously evaluate models to identify and rectify errors. Maintain the integrity of our data-driven decisions through high performance and reliability. Efficiency and Scalability: Streamline processes to reduce time-to-market. Scale AI initiatives and ML engineering skills effectively with dedicated model training and testing. 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