1668 Mlflow Jobs - Page 23

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

We are looking for an enthusiastic AI/ML Developer with 3-5 years of experience to design, develop, and deploy AI/ML solutions. The ideal candidate is passionate about AI, skilled in machine learning, deep learning, and MLOps, and eager to work on cutting-edge projects. Key Skills & Experience: Programming: Python (TensorFlow, PyTorch, Scikit-learn, Pandas). Machine Learning: Supervised, Unsupervised, Deep Learning, NLP, Computer Vision. Model Deployment: Flask, FastAPI, AWS SageMaker, Google Vertex AI, Azure ML. MLOps & Cloud: Docker, Kubernetes, MLflow, Kubeflow, CI/CD pipelines. Big Data & Databases: Spark, Dask, SQL, NoSQL (PostgreSQL, MongoDB). Soft Skills: Strong analytical and problem-solving mindset. Passion for AI innovation and continuous learning. Excellent teamwork and communication abilities. Qualifications: Bachelor's/Master's in Computer Science, AI, Data Science, or related fields. AI/ML certifications are a plus. Career Level - IC4 We are looking for an enthusiastic AI/ML Developer with 3-5 years of experience to design, develop, and deploy AI/ML solutions. The ideal candidate is passionate about AI, skilled in machine learning, deep learning, and MLOps, and eager to work on cutting-edge projects. Key Skills & Experience: Programming: Python (TensorFlow, PyTorch, Scikit-learn, Pandas). Machine Learning: Supervised, Unsupervised, Deep Learning, NLP, Computer Vision. Model Deployment: Flask, FastAPI, AWS SageMaker, Google Vertex AI, Azure ML. MLOps & Cloud: Docker, Kubernetes, MLflow, Kubeflow, CI/CD pipelines. Big Data & Databases: Spark, Dask, SQL, NoSQL (PostgreSQL, MongoDB). Soft Skills: Strong analytical and problem-solving mindset. Passion for AI innovation and continuous learning. Excellent teamwork and communication abilities. Qualifications: Bachelor's/Master's in Computer Science, AI, Data Science, or related fields. AI/ML certifications are a plus. Diversity & Inclusion: An Oracle career can span industries, roles, Countries and cultures, giving you the opportunity to flourish in new roles and innovate, while blending work life in. Oracle has thrived through 40+ years of change by innovating and operating with integrity while delivering for the top companies in almost every industry. In order to nurture the talent that makes this happen, we are committed to an inclusive culture that celebrates and values diverse insights and perspectives, a workforce that inspires thought leadership and innovation. . Oracle offers a highly competitive suite of Employee Benefits designed on the principles of parity, consistency, and affordability. The overall package includes certain core elements such as Medical, Life Insurance, access to Retirement Planning, and much more. We also encourage our employees to engage in the culture of giving back to the communities where we live and do business. At Oracle, we believe that innovation starts with diversity and inclusion and to create the future we need talent from various backgrounds, perspectives, and abilities. We ensure that individuals with disabilities are provided reasonable accommodation to successfully participate in the job application, interview process, and in potential roles. to perform crucial job functions. That's why we're committed to creating a workforce where all individuals can do their best work. It's when everyone's voice is heard and valued that we're inspired to go beyond what's been done before.

About Enqurious Enqurious (formerly Mentorskool) is a fast-growing EdTech company based in Bengaluru that specializes in upskilling industry-ready Data + AI teams. We combine skill-driven precision learning with data-driven skill intelligence to help organizations deploy talent to projects 70% faster. Our mission is to bridge the skills gap in the data + AI space through problem-first, action-oriented, and mentorship-driven learning experiences. Our clientele includes large Enterprise Data and AI consulting firms like Fractal Analytics, Tredence, Tiger Analytics and MathCo. We help our customers achieve upskilling in many different flavors including - Graduate Data Engineer Upskilling, Continuous Learning, Certifications, Hackathons and Project Accelerators. Enqurious is our home-grown Learning Engagement Platform where we put well researched learning experiences integrated with labs to help learners experience real-world problems and challenges leading to upskilling that delivers business outcomes. https://www.enqurious.com/ Position Overview Location: Bengaluru, Karnataka (Hybrid) Experience: 2+ years Employment Type: Full-time Department: AI & ML We are seeking a passionate Data Scientist with 2+ years of experience to join our core team. This role offers a unique opportunity to work on cutting-edge data science projects and contribute to shaping the next generation of data professionals through developing domain first use cases and delivered via mentoring Must-Have Requirements Technical Skills SQL Mastery: Advanced proficiency in SQL with experience in complex query optimization, performance tuning, and working with large datasets and relational data modelling Statistical & ML Foundations: Strong grasp of probability, statistics, hypothesis testing, and ML algorithms (supervised, unsupervised, and time-series). Python Programming: Proficiency with pandas, NumPy, scikit-learn, TensorFlow/PyTorch, and data-validation/automation scripting. Data Visualisation: Ability to craft compelling stories with Matplotlib, Seaborn, Plotly Cloud Fundamentals: Solid understanding of cloud computing principles, Familiarity with ML services on AWS (SageMaker, Athena), or Azure (ML Studio, Databricks). Experience & Mindset - Must have Minimum 2 years of hands-on data science experience with a proven track record of building models and MLOps pipelines Model Development & Deployment: Experience building robust, scalable MLops on cloud platforms, preferably AWS (S3, Sagemaker) or Azure(Adls, Databricks, MLflow, Azure ML Studio) Continuous Learning: Demonstrated ability to quickly adapt to new technologies, frameworks, and methodologies in the rapidly evolving data landscape Teaching/Mentoring Aptitude : Genuine interest and willingness to occasionally conduct corporate training sessions, workshops Ability to work in uncertain and ambiguous environments. We expect you to be a self-starter, and you will be required to demonstrate this skill in the interview Good to Have Startup Mindset: Openness to work closely with core and founding team members in creating RFPs, proposals, and strategic technical documents Client Interaction: Experience interfacing with clients to understand requirements and translate business needs into technical solutions Key Responsibilities Core Engineering (for experience building and creating simulated projects inspired by the real world) Design, build, and maintain reproducible ML pipelines (feature engineering, training, evaluation, and CI/CD deployment). Develop predictive, prescriptive, and generative models that are performant, explainable, and cost-efficient. Implement data-quality checks, bias/variance monitoring, and automated drift detection. Conduct mentoring sessions on data science best practices, tools, and technologies Develop hands-on labs and real-world scenarios for upskilling programs Contribute to Enqurious's knowledge base and learning content library Strategic Contributions Participate in technical discussions with the founding team and contribute to content roadmap decisions Assist in creating technical proposals, RFPs, and solution architectures for enterprise clients for their upskilling needs Stay updated with industry trends and emerging technologies to enhance our training offerings Represent Enqurious at technical conferences, meetups, and community events What We Offer Professional Growth Accelerated Learning Environment: Work alongside industry experts and gain exposure to diverse data science challenges across multiple domains (Retail, CPG, E-Commerce, FinTech, Insurance) Mentoring Opportunities: Develop your communication and leadership skills through corporate training and mentoring Industry Recognition: Opportunity to build your brand in the data science community Certification Support: Access to premium training resources and certification programs (Databricks, AWS, Azure) Work Environment Flexible Work Arrangements: Hybrid working model with collaborative office environment in Bengaluru Innovation Culture: Be part of a team that's disrupting traditional corporate learning methodologies Direct Impact: Your work will directly influence how thousands of data scientists are trained globally Startup Agility: Fast-paced environment with opportunities to wear multiple hats and drive initiatives Compensation & Benefits Competitive salary commensurate with experience and skills Performance-based bonuses and equity opportunities Health insurance and wellness programs Professional development budget for conferences, courses, and certifications Ideal Candidate Profile You're the perfect fit if you: Love building impactful models and sharing knowledge Thrive in ambiguous, fast-paced environments where you can make a significant impact Enjoy collaborating with diverse teams, including educators, business stakeholders, and technical experts We are excited about the intersection of technology and education Have a growth mindset and are energized by continuous learning and teaching Can balance hands-on technical work with strategic thinking and planning Application Process 1-2 Interview rounds. Please note that we are only willing to accept anyone who has a notice period of 30 days or less How to Apply? If you're excited about the opportunity to build cutting-edge data solutions while shaping the future of Data Science + AI education, we'd love to hear from you. Apply with your resume, a brief cover letter explaining your interest in this unique role, and any relevant project portfolios or certifications. Send your updated resume to learn@enqurious.com with the subject line "Application for Data Scientist - ." Enqurious is an equal opportunity employer committed to diversity and inclusion. We encourage applications from all qualified candidates regardless of race, gender, age, religion, sexual orientation, or disability status.

This role is for one of Weekday's clients Min Experience: 2 years Location: gurugram, NCR, Delhi, NOIDA, Uttar Pradesh JobType: full-time Requirements About the Role: We are seeking a passionate and skilled AI/ML Engineer with 2+ years of experience to join our growing technology team. The ideal candidate will have a strong foundation in machine learning, data processing, and model deployment. You will work on developing and implementing cutting-edge AI and ML models to solve real-world problems and contribute to the development of intelligent systems across our product suite. You'll collaborate with cross-functional teams including data scientists, software engineers, and product managers to build scalable and robust ML-powered applications. Key Responsibilities: 🔹 Model Development & Deployment Design, build, and train machine learning models to support core product features. Experiment with supervised, unsupervised, and deep learning algorithms to solve business challenges. Deploy models into production environments and monitor their performance. 🔹 Data Handling & Feature Engineering Collect, clean, preprocess, and analyze large volumes of structured and unstructured data. Engineer features that enhance model performance and align with product requirements. Ensure data quality and consistency across the pipeline. 🔹 Model Optimization Evaluate model performance using relevant metrics (precision, recall, F1-score, ROC-AUC, etc.). Optimize models for speed and accuracy using hyperparameter tuning, ensemble methods, or transfer learning. 🔹 Collaboration & Integration Collaborate with backend and frontend teams to integrate AI/ML capabilities into products. Build APIs and services that expose ML models for consumption across applications. Work closely with data engineers and DevOps to deploy and scale ML pipelines. 🔹 Research & Innovation Stay updated on the latest trends, tools, and frameworks in AI/ML. Prototype and test innovative AI solutions, including NLP, computer vision, recommendation systems, or time series forecasting. Document methodologies, findings, and technical processes clearly. Skills & Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field. 2+ years of hands-on experience in AI/ML model development and deployment. Strong knowledge of Python and ML libraries such as scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, or similar. Experience with data manipulation tools like Pandas, NumPy, and visualization libraries such as Matplotlib or Seaborn. Understanding of ML lifecycle, including data preprocessing, model building, evaluation, and deployment. Familiarity with cloud platforms (AWS, GCP, Azure) and container technologies like Docker is a plus. Knowledge of REST APIs and integration of ML models with applications. Excellent problem-solving and analytical skills. Strong communication skills and ability to explain complex ML concepts to non-technical stakeholders. Preferred (Nice to Have): Experience with Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning. Exposure to MLOps, model monitoring, or CI/CD pipelines. Familiarity with data versioning tools like DVC, MLflow, or Kubeflow

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

This role is for one of Weekday's clients Min Experience: 2 years Location: gurugram, NCR, Delhi, NOIDA, Uttar Pradesh JobType: full-time Requirements About the Role: We are seeking a passionate and skilled AI/ML Engineer with 2+ years of experience to join our growing technology team. The ideal candidate will have a strong foundation in machine learning, data processing, and model deployment. You will work on developing and implementing cutting-edge AI and ML models to solve real-world problems and contribute to the development of intelligent systems across our product suite. You'll collaborate with cross-functional teams including data scientists, software engineers, and product managers to build scalable and robust ML-powered applications. Key Responsibilities: 🔹 Model Development & Deployment Design, build, and train machine learning models to support core product features. Experiment with supervised, unsupervised, and deep learning algorithms to solve business challenges. Deploy models into production environments and monitor their performance. 🔹 Data Handling & Feature Engineering Collect, clean, preprocess, and analyze large volumes of structured and unstructured data. Engineer features that enhance model performance and align with product requirements. Ensure data quality and consistency across the pipeline. 🔹 Model Optimization Evaluate model performance using relevant metrics (precision, recall, F1-score, ROC-AUC, etc.). Optimize models for speed and accuracy using hyperparameter tuning, ensemble methods, or transfer learning. 🔹 Collaboration & Integration Collaborate with backend and frontend teams to integrate AI/ML capabilities into products. Build APIs and services that expose ML models for consumption across applications. Work closely with data engineers and DevOps to deploy and scale ML pipelines. 🔹 Research & Innovation Stay updated on the latest trends, tools, and frameworks in AI/ML. Prototype and test innovative AI solutions, including NLP, computer vision, recommendation systems, or time series forecasting. Document methodologies, findings, and technical processes clearly. Skills & Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field. 2+ years of hands-on experience in AI/ML model development and deployment. Strong knowledge of Python and ML libraries such as scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, or similar. Experience with data manipulation tools like Pandas, NumPy, and visualization libraries such as Matplotlib or Seaborn. Understanding of ML lifecycle, including data preprocessing, model building, evaluation, and deployment. Familiarity with cloud platforms (AWS, GCP, Azure) and container technologies like Docker is a plus. Knowledge of REST APIs and integration of ML models with applications. Excellent problem-solving and analytical skills. Strong communication skills and ability to explain complex ML concepts to non-technical stakeholders. Preferred (Nice to Have): Experience with Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning. Exposure to MLOps, model monitoring, or CI/CD pipelines. Familiarity with data versioning tools like DVC, MLflow, or Kubeflow

This role is for one of Weekday's clients Min Experience: 2 years Location: gurugram, NCR, Delhi, NOIDA, Uttar Pradesh JobType: full-time Requirements About the Role: We are seeking a passionate and skilled AI/ML Engineer with 2+ years of experience to join our growing technology team. The ideal candidate will have a strong foundation in machine learning, data processing, and model deployment. You will work on developing and implementing cutting-edge AI and ML models to solve real-world problems and contribute to the development of intelligent systems across our product suite. You'll collaborate with cross-functional teams including data scientists, software engineers, and product managers to build scalable and robust ML-powered applications. Key Responsibilities: 🔹 Model Development & Deployment Design, build, and train machine learning models to support core product features. Experiment with supervised, unsupervised, and deep learning algorithms to solve business challenges. Deploy models into production environments and monitor their performance. 🔹 Data Handling & Feature Engineering Collect, clean, preprocess, and analyze large volumes of structured and unstructured data. Engineer features that enhance model performance and align with product requirements. Ensure data quality and consistency across the pipeline. 🔹 Model Optimization Evaluate model performance using relevant metrics (precision, recall, F1-score, ROC-AUC, etc.). Optimize models for speed and accuracy using hyperparameter tuning, ensemble methods, or transfer learning. 🔹 Collaboration & Integration Collaborate with backend and frontend teams to integrate AI/ML capabilities into products. Build APIs and services that expose ML models for consumption across applications. Work closely with data engineers and DevOps to deploy and scale ML pipelines. 🔹 Research & Innovation Stay updated on the latest trends, tools, and frameworks in AI/ML. Prototype and test innovative AI solutions, including NLP, computer vision, recommendation systems, or time series forecasting. Document methodologies, findings, and technical processes clearly. Skills & Qualifications: Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field. 2+ years of hands-on experience in AI/ML model development and deployment. Strong knowledge of Python and ML libraries such as scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, or similar. Experience with data manipulation tools like Pandas, NumPy, and visualization libraries such as Matplotlib or Seaborn. Understanding of ML lifecycle, including data preprocessing, model building, evaluation, and deployment. Familiarity with cloud platforms (AWS, GCP, Azure) and container technologies like Docker is a plus. Knowledge of REST APIs and integration of ML models with applications. Excellent problem-solving and analytical skills. Strong communication skills and ability to explain complex ML concepts to non-technical stakeholders. Preferred (Nice to Have): Experience with Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning. Exposure to MLOps, model monitoring, or CI/CD pipelines. Familiarity with data versioning tools like DVC, MLflow, or Kubeflow

Job Description: We are looking for a passionate and skilled AI Developer with 3–4 years of hands-on experience to join our dynamic team. The ideal candidate must have a strong foundation in Python and a proven track record of developing and deploying AI/ML solutions. You will be responsible for designing intelligent systems, training models, and collaborating with cross-functional teams to implement AI-driven features in our products. Key Responsibilities: Design, develop, and deploy machine learning and deep learning models. Collaborate with data scientists and software engineers to build AI-powered applications. Perform data wrangling, preprocessing, and feature engineering on large datasets. Evaluate model performance using appropriate metrics and optimize accordingly. Integrate AI models into production using APIs or ML frameworks. Research and implement the latest AI technologies and best practices. Maintain and improve existing AI systems for performance and scalability. Document solutions and write clean, maintainable code. Required Skills & Qualifications: 3–4 years of experience in AI/ML development. Strong proficiency in Python and its AI/ML libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). Solid understanding of machine learning algorithms, data structures, and OOP principles. Experience with NLP, computer vision, or generative AI is a plus. Familiarity with model deployment frameworks (e.g., Flask, FastAPI, Docker). Experience with version control systems like Git. Good knowledge of databases (SQL/NoSQL) and data pipelines. Excellent problem-solving skills and attention to detail. Preferred Qualifications: Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field. Experience with cloud platforms like AWS, Azure, or GCP. Understanding of MLOps concepts and tools (e.g., MLflow, Kubeflow). Exposure to agile development environments. Job Type: Full-time Pay: ₹65,000.00 - ₹85,000.00 per month Benefits: Flexible schedule Location Type: In-person Schedule: Day shift Work Location: In person

About Us: At HCL-GUVI, we are on a mission to empower organizations with cutting-edge AI and ML capabilities. We work closely with Fortune 500 companies to upskill their workforce through customized, high-impact training solutions. If you’re passionate about AI/ML education and want to work with the R&D segment of one of the fastest-growing corporate training arms, we want to hear from you! Job Title: Technical Subject Matter Expert – AI & Machine Learning Location: On-site/Hybrid (Based on corporate training location) Organization: HCL-GUVI Role Overview: We are seeking a Subject Matter Expert (SME) in Artificial Intelligence and Machine Learning to lead and deliver corporate training programs. The ideal candidate will possess deep domain knowledge, real-world experience, and a strong passion for teaching and innovation. Key Responsibilities: ● Training Delivery: Conduct high-quality, in-depth AI/ML training sessions for corporate employees (on-site or virtually). ● Curriculum Design: Collaborate with stakeholders to create and customize training modules tailored to business needs. ● Project Development: Design industry-relevant, state-of-the-art AI/ML/Generative AI projects and hands-on tasks. ● Assessment & Evaluation: Systematically evaluate learners' progress, conduct code reviews, and provide constructive feedback. ● R&D Collaboration: Work with HCL-GUVI's R&D teams to stay updated with emerging trends and technologies. ● Mentorship: Guide and mentor junior trainers, interns, or learners as needed. Required Qualifications: ● Education: ○ Bachelor’s/Master’s in Computer Science, Artificial Intelligence, Applied Statistics, Data Science, or related fields. ○ Preferred from Tier-1 institutions (IITs, NITs, IIITs, IISc, etc.). ● Experience: ○ 3–5+ years of hands-on industry experience (both in Corporate project development & Corporate training) in AI, Machine Learning, or MLOps. ○ Experience in training corporate employees or holding academic/training positions is a must. Skills and Competencies: ● Technical Skills: ○ Strong understanding of Machine Learning, Deep Learning, Generative AI (LLMs, Transformers, etc.), and MLOps. ○ Expertise in Python, TensorFlow, PyTorch, Scikit-learn, Hugging Face, OpenAI APIs, LangChain, etc. ○ Familiarity with cloud platforms (AWS, Azure, GCP) and ML pipelines. ● Training & Communication: ○ Excellent presentation, instructional design, and communication skills. ○ Proven ability to explain complex concepts in simple terms to a non-technical audience. ● Project Skills: ○ Ability to design real-world capstone projects, datasets, and evaluation metrics. ○ Experience with version control (Git), Docker, CI/CD for ML, and experiment tracking tools (MLflow, Weights & Biases). Preferred Skills: ● Experience with Generative AI, Prompt Engineering, Retrieval-Augmented Generation (RAG), and LLM fine-tuning. ● Exposure to data governance, ethical AI, and explainable AI (XAI) principles. ● Knowledge of corporate L&D processes and success metrics. Why Join Us? ● Competitive Salary aligned with industry standards. ● Access to cutting-edge R&D projects at the intersection of AI and enterprise solutions. ● Opportunity to collaborate with global clients and leading consulting firms (EY, Deloitte, etc.). ● High visibility role with opportunities for growth and leadership. ● Engaging work culture that values innovation, learning, and impact. Apply Now and become a part of the future of AI-driven corporate learning! Job Types: Full-time, Permanent Pay: ₹2,500,000.00 - ₹3,000,000.00 per year Benefits: Health insurance Schedule: Day shift Morning shift Work Location: In person Application Deadline: 10/07/2025 Expected Start Date: 21/07/2025

About the Role: We are looking for a highly skilled and forward-thinking AI/ML Engineer with 3–4 years of practical experience in building and deploying AI-powered solutions for industrial automation, computer vision, and LLM-based applications. The ideal candidate should have experience with the latest AI tools and frameworks including LangChain, LangGraph, Vision Transformers, and MLOps on AWS (SageMaker), as well as expertise in building multi-agent chat applications with React agents and vector-based RAG (Retrieval-Augmented Generation) architectures. Responsibilities: · Design, train, and deploy AI/ML models for industrial automation, including computer vision systems using OpenCV and deep learning frameworks. · Develop multi-agent chat applications integrating LLMs, React-based agents, and contextual memory. · Implement Vision Transformers (ViTs) for advanced visual understanding tasks. · Utilize LangChain, LangGraph, and RAG techniques to create intelligent conversational systems with vector embeddings and document retrieval. · Fine-tune pre-trained LLMs for custom enterprise use cases. · Collaborate with frontend teams to build responsive, intelligent UIs using React + AI backends. · Deploy AI solutions on AWS Cloud, leveraging SageMaker, Lambda, S3, and related MLOps tools for model lifecycle management. · Ensure high performance, reliability, and scalability of deployed AI systems. Required Skills · 3–4 years of hands-on experience in AI/ML engineering, preferably with industrial or automation-focused projects. · Proficiency in Python and frameworks like PyTorch, TensorFlow, Scikit-learn. · Strong understanding of LLMs (GPT, Claude, LLaMA, etc.), prompt engineering, and fine-tuning techniques. · Experience with LangChain, LangGraph, and RAG-based architecture using vector databases like FAISS, Pinecone, or Weaviate. · Expertise in Vision Transformers, YOLO, Detectron2, and computer vision techniques. · Familiarity with multi-agent architectures, React agents, and building intelligent UIs with frontend-backend synergy. · Working knowledge of AWS services (SageMaker, Lambda, EC2, S3) and MLOps workflows (CI/CD for ML). · Experience deploying and maintaining models in production environments. Qualifications: · Experience with edge AI, NVIDIA Jetson, or industrial IoT integration. · Prior involvement in developing AI-powered chatbots or assistants with memory and tool integration. · Exposure to containerization (Docker) and model versioning tools like MLflow or DVC. · Contributions to open-source AI projects or published research in AI/ML Job Type: Full-time Pay: From ₹412,334.30 per year Benefits: Health insurance Paid sick time Provident Fund Schedule: Day shift Supplemental Pay: Performance bonus Ability to commute/relocate: Indore, Madhya Pradesh: Reliably commute or planning to relocate before starting work (Required) Work Location: In person

Job Description for Databricks Platform Administrator Experience Level: 8-12 Yrs Job Title: Databricks Platform Administrator Roles and Responsibilities A Databricks Platform Administrator is a crucial role responsible for the effective design, implementation, maintenance, and optimization of the Databricks Lakehouse Platform within an organization. This individual ensures the platform is scalable, performant, secure, and aligned with business objectives, providing essential support to data engineers, data scientists, and analysts. Job Summary: The Databricks Platform Administrator is a key member of our data and analytics team, responsible for the overall administration, configuration, and optimization of the Databricks Lakehouse Platform. This role ensures the platform's stability, security, and performance, enabling data engineering, data science, and machine learning initiatives. The administrator will work closely with various cross-functional teams to understand requirements, provide technical solutions, and maintain best practices for the Databricks environment. Key Responsibilities: 1. Provision and configure Databricks workspaces, clusters, pools, and jobs across environments. 2. Create catalogs, schemas, access controls, and lineage configurations. 3. Implement identity and access management using account groups, workspace-level permissions, and data-level governance. 4. Monitor platform health, cluster utilization, job performance, and cost using Databricks admin tools and observability dashboards. 5. Automate workspace onboarding, schema creation, user/group assignments, and external location setup using Terraform, APIs, or CLI. 6. Integrate with Azure services like ADLS Gen2, Azure Key Vault, Azure Data Factory, and Azure Synapse. 7. Support model serving, feature store, and MLflow lifecycle management for Data Science/ML teams. 8. Manage secrets, tokens, and credentials securely using Databricks Secrets and integration with Azure Key Vault. 9. Define and enforce tagging policies, data masking, and row-level access control using Unity Catalog and Attribute-Based Access Control (ABAC). 10. Ensure compliance with enterprise policies, security standards, and audit requirements. 11. Coordinate with Ops Architect, Cloud DevOps teams for network, authentication (e.g., SSO), and VNET setup. 12. Troubleshoot workspace, job, cluster, or permission issues for end users and data teams. Preferred Qualifications: · Databricks Certified Associate Platform Administrator or other relevant Databricks certifications. · Experience with Apache Spark and data engineering concepts. · Knowledge of monitoring tools (e.g., Splunk, Grafana, Cloud-native monitoring). · Familiarity with data warehousing and data lake concepts. · Experience with other big data technologies (e.g., Hadoop, Kafka). · Previous experience leading or mentoring junior administrators.

AI Engineer – Voice, NLP, and GenAI Systems Location : Sector 63, Gurgaon – 100% In-Office Working Days : Monday to Friday, with 2nd and 4th Saturdays off Working Hours : 10:30 AM to 8:00 PM Experience : 2–6 years in AI/ML, NLP, or applied machine learning engineering Apply at : careers@darwix.ai Subject Line : Application – AI Engineer – [Your Name] About Darwix AI Darwix AI is India’s fastest-growing GenAI SaaS platform transforming how enterprise sales, field, and support teams engage with customers. Our suite— Transform+ , Sherpa.ai , and Store Intel —powers real-time multilingual voice analytics, AI nudges, coaching systems, and computer vision analytics for major enterprises across India, MENA, and Southeast Asia. We work with some of the largest names such as Aditya Birla Capital, Sobha, GIVA, and Bank Dofar. Our systems process thousands of daily conversations, live call transcripts, and omnichannel data to deliver actionable revenue insights and in-the-moment enablement. Role Overview As an AI Engineer , you will play a key role in designing, developing, and scaling AI and NLP systems that power our core products. You will work at the intersection of voice AI, natural language processing (NLP), large language models (LLMs), and speech-to-text pipelines. You will collaborate with product, backend, and frontend teams to integrate ML models into production workflows, optimize inference pipelines, and improve the accuracy and performance of real-time analytics used by enterprise sales and field teams. Key ResponsibilitiesAI & NLP System Development Design, train, fine-tune, and deploy NLP models for conversation analysis, scoring, sentiment detection, and call summarization. Work on integrating and customizing speech-to-text (STT) pipelines (e.g., WhisperX, Deepgram) for multilingual audio data. Develop and maintain classification, extraction, and sequence-to-sequence models to handle real-world sales and service conversations. LLM & Prompt Engineering Experiment with and integrate large language models (OpenAI, Cohere, open-source LLMs) for live coaching and knowledge retrieval use cases. Optimize prompts and design retrieval-augmented generation (RAG) workflows to support real-time use in product modules. Develop internal tools for model evaluation and prompt performance tracking. Productionization & Integration Build robust model APIs and microservices in collaboration with backend engineers (primarily Python, FastAPI). Optimize inference time and resource utilization for real-time and batch processing needs. Implement monitoring and logging for production ML systems to track drift and failure cases. Data & Evaluation Work on audio-text alignment datasets, conversation logs, and labeled scoring data to improve model performance. Build evaluation pipelines and create automated testing scripts for accuracy and consistency checks. Define and track key performance metrics such as WER (word error rate), intent accuracy, and scoring consistency. Collaboration & Research Work closely with product managers to translate business problems into model design requirements. Explore and propose new approaches leveraging the latest research in voice, NLP, and generative AI. Document research experiments, architecture decisions, and feature impact clearly for internal stakeholders. Required Skills & Qualifications 2–6 years of experience in AI/ML engineering, preferably with real-world NLP or voice AI applications. Strong programming skills in Python , including libraries like PyTorch, TensorFlow, Hugging Face Transformers. Experience with speech processing , audio feature extraction, or STT pipelines. Solid understanding of NLP tasks: tokenization, embedding, NER, summarization, intent detection, sentiment analysis. Familiarity with deploying models as APIs and integrating them with production backend systems. Good understanding of data pipelines, preprocessing techniques, and scalable model architectures. Preferred Qualifications Prior experience with multilingual NLP systems or models tuned for Indian languages. Exposure to RAG pipelines , embeddings search (e.g., FAISS, Pinecone), and vector databases. Experience working with voice analytics, diarization, or conversational scoring frameworks. Understanding of DevOps basics for ML (MLflow, Docker, GitHub Actions for model deployment). Experience in SaaS product environments serving enterprise clients. Success in This Role Means Accurate, robust, and scalable AI models powering production workflows with minimal manual intervention. Inference pipelines optimized for enterprise-scale deployments with high availability. New features and improvements delivered quickly to drive direct business impact. AI-driven insights and automations that enhance user experience and boost revenue outcomes for clients. You Will Excel in This Role If You Love building AI systems that create measurable value in the real world, not just in research labs. Enjoy solving messy, real-world data problems and working on multilingual and noisy data. Are passionate about voice and NLP, and constantly follow advancements in GenAI. Thrive in a fast-paced, high-ownership environment where ideas quickly become live features. How to Apply Email your updated CV to careers@darwix.ai Subject Line: Application – AI Engineer – [Your Name] (Optional): Share links to your GitHub, open-source contributions, or a short note about a model or system you designed and deployed in production. This is an opportunity to build foundational AI systems at one of India’s fastest-scaling GenAI startups and to impact how large enterprises engage millions of customers every day. If you are ready to transform how AI meets revenue teams—Darwix AI wants to hear from you.

The Opportunity Are you passionate about building intelligent, enterprise-grade AI systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic frameworks? At Nutanix, we're looking for a skilled and experienced AI/ML engineer to help shape the future of generative AI within our SaaS Engineering organization. As a senior member of our team, youll work at the cutting edge of AI innovationdeveloping and deploying state-of-the-art LLMs and embedding models, optimizing model performance, and building scalable ML pipelines with real-world impact. About the Team At Nutanix, you will be joining a dynamic central platform team that plays a pivotal role in revolutionizing our approach to artificial intelligence and machine learning within the SaaS Engineering group. Comprising eight experienced engineers, our team specializes in addressing the GenAI, machine learning, and data science needs of various squads within the organization. Our diverse skill set ensures we collaborate effectively to create innovative solutions, leveraging the latest advancements in technology to drive our initiatives forward. Your Role Design and deploy Retrieval-Augmented Generation (RAG) pipelines . Build, fine-tune, and deploy LLMs and embedding models such as LLaMA 3 , Gemma , Mistral , and other domain-specific transformers. Fine-tune both LLMs and embedding models for specialized enterprise tasks including Q&A, summarization, classification, and conversational AI. Develop and maintain agentic frameworks capable of orchestrating task-specific intelligent agents with memory, planning, and tool-use capabilities. Build and evaluate custom agents for use cases like document analysis, data querying, and interactive user support. Implement evaluation frameworks for LLM outputs, including both automated metrics and task-specific success criteria. Work closely with data engineering teams to develop custom training pipelines and extract meaningful insights from large-scale internal datasets. Develop MLOps pipelines for training, deployment, and monitoring using tools like MLflow , Kubeflow , and custom CI/CD workflows. Deploy optimized inference endpoints for high-performance, low-latency model serving at scale. Manage vectorization workflows using advanced embedding models and vector databases for semantic search and content retrieval. Demonstrate working knowledge of LangChain, OpenAI function-calling, vector databases and scalable retrieval logic. Work with Kubernetes clusters to provision, scale, and monitor AI/ML workloads; understand GPU, CPU, and storage hardware requirements for efficient deployment. Collaborate with cross-functional teams including backend, data, and infrastructure engineers to integrate models seamlessly into production systems. What You Will Bring Bachelors, Masters, or Ph.D. in Computer Science, Machine Learning, Applied Math, or a related field. 5+ years of hands-on experience building, deploying, and maintaining AI/ML systems in production environments. Strong foundation in MLOps, including model versioning, CI/CD, monitoring, and retraining workflows. In-depth understanding of Kubernetes (K8s) and GPU-based infrastructure, including container orchestration and GPU scheduling for AI workloads. Experience working with Elasticsearch for semantic search and integrating it within RAG or LLM-driven architectures. Proficient in Python (core ML libraries like PyTorch, Pandas, and NumPy). Hands-on experience using Jupyter Notebooks for experimentation, documentation, and collaboration. Comfortable with Unix-based systems, shell scripting, and command-line tooling for ML operations and debugging. Familiarity with LangChain, LLM orchestration, and vector database integration. Strong collaboration and communication skills, with the ability to mentor junior team members and drive initiatives independently. Open-source contributions or published work in the ML/AI domain is a plus.

Role name: Automation Test Lead (AI/ML) Years of exp: 5 - 8 yrs About Dailoqa Dailoqa’s mission is to bridge human expertise and artificial intelligence to solve the challenges facing financial services. Our founding team of 20+ international leaders, including former CIOs and senior industry experts, combines extensive technical expertise with decades of real-world experience to create tailored solutions that harness the power of combined intelligence. With a focus on Financial Services clients, we have deep expertise across Risk & Regulations, Retail & Institutional Banking, Capital Markets, and Wealth & Asset Management. Dailoqa has global reach in UK, Europe, Africa, India, ASEAN, and Australia. We integrate AI into business strategies to deliver tangible outcomes and set new standards for the financial services industry. Working at Dailoqa will be hard work, our environment is fluid and fast-moving and you'll be part of a community that values innovation, collaboration, and relentless curiosity. We’re looking at people who: Are proactive, curious adaptable, and patient Shape the company's vision and will have a direct impact on its success. Have the opportunity for fast career growth. Have the opportunity to participate in the upside of an ultra-growth venture. Have fun 🙂 Don’t apply if: You want to work on a single layer of the application. You prefer to work on well-defined problems. You need clear, pre-defined processes. You prefer a relaxed and slow paced environment. Role Overview As an Automation Test Lead at Dailoqa, you’ll architect and implement robust testing frameworks for both software and AI/ML systems. You’ll bridge the gap between traditional QA and AI-specific validation, ensuring seamless integration of automated testing into CI/CD pipelines while addressing unique challenges like model accuracy, GenAI output validation, and ethical AI compliance. Key Responsibilities Test Automation Strategy & Framework Design Design and implement scalable test automation frameworks for frontend (UI/UX), backend APIs, and AI/ML model-serving endpoints using tools like Selenium, Playwright, Postman, or custom Python/Java solutions. Build GenAI-specific test suites for validating prompt outputs, LLM-based chat interfaces, RAG systems, and vector search accuracy. Develop performance testing strategies for AI pipelines (e.g., model inference latency, resource utilization). Continuous Testing & CI/CD Integration Establish and maintain continuous testing pipelines integrated with GitHub Actions, Jenkins, or GitLab CI/CD. Implement shift-left testing by embedding automated checks into development workflows (e.g., unit tests, contract testing). AI/ML Model Validation Collaborate with data scientists to test AI/ML models for accuracy, fairness, stability, and bias mitigation using tools like TensorFlow Model Analysis or MLflow. Validate model drift and retraining pipelines to ensure consistent performance in production. Quality Metrics & Reporting Define and track KPIs: Test coverage (code, data, scenarios) Defect leakage rate Automation ROI (time saved vs. maintenance effort) Model accuracy thresholds Report risks and quality trends to stakeholders in sprint reviews. Drive adoption of AI-specific testing tools (e.g., LangChain for LLM testing, Great Expectations for data validation). Technical Requirements Must-Have 5–8 years in test automation, with 2+ years validating AI/ML systems. Expertise in: Automation tools: Selenium, Playwright, Cypress, REST Assured, Locust/JMeter CI/CD: Jenkins, GitHub Actions, GitLab AI/ML testing: Model validation, drift detection, GenAI output evaluation Languages: Python, Java, or JavaScript Certifications: ISTQB Advanced, CAST, or equivalent. Experience with MLOps tools: MLflow, Kubeflow, TFX Familiarity with vector databases (Pinecone, Milvus) and RAG workflows. Strong programming/scripting experience in JavaScript, Python, Java, or similar Experience with API testing, UI testing, and automated pipelines Understanding of AI/ML model testing, output evaluation, and non-deterministic behavior validation Experience with testing AI chatbots, LLM responses, prompt engineering outcomes, or AI fairness/bias Familiarity with MLOps pipelines and automated validation of model performance in production Exposure to Agile/Scrum methodology and tools like Azure Boards Soft Skills Strong problem-solving skills for balancing speed and quality in fast-paced AI development. Ability to communicate technical risks to non-technical stakeholders. Collaborative mindset to work with cross-functional teams (data scientists, ML engineers, DevOps).

Job Description: We are seeking a results-driven AI with Python Team Lead on immediate basis who can guide a team of AI engineers and independently manage AI/ML projects particularly in adverse media analysis, risk intelligence, and data-driven compliance solutions . The ideal candidate will have a solid foundation in Python-based AI/ML development and hands-on experience working with unstructured data sources for screening, classification, and risk identification. Candidates who can join immediately will be preferred. Responsibilities Lead a team of AI/ML engineers focused on building intelligent systems, particularly for Adverse Media detection and analysis . Develop and deploy scalable AI/ML models using Python to analyze structured and unstructured media sources. Build and optimize NLP pipelines for entity extraction, sentiment analysis, and news classification. Architect and implement solutions that classify and score entities (individuals or companies) based on risk. Translate compliance and regulatory requirements into AI-powered systems. Independently handle project lifecycles from scoping and design to delivery and optimization. Mentor junior team members and enforce best practices in AI development. Conduct regular performance reviews, knowledge sharing, and skill development sessions within the team. Collaborate with cross-functional teams including Data Associates, and QA. Document AI systems, model decisions, and ensure auditability of outputs. Qualifications and Required Skills Bachelor’s or Master’s in Computer Science with AI Specialization. 4 years of hands-on experience in Python-based AI/ML development. Strong experience in Adverse Media , KYC, AML, or regulatory intelligence. Proficiency in NLP, text classification, named entity recognition (NER), topic modeling, and sentiment analysis. Strong command of Python libraries like SpaCy, Transformers (Hugging Face), Scikit-learn, Pandas, NumPy , etc. Experience handling multilingual media sources and identifying fake, biased, or non-reputable sources. Familiarity with risk scoring methodologies, sanctions screening, or negative news processing. Preferred Skills: Experience working with third-party adverse media feeds or OSINT platforms. Exposure to ML pipelines (MLflow, Airflow) and MLOps practices. Familiarity with graph databases and link analysis for network detection (e.g., Neo4j, NetworkX). Experience in working with Tor network data, onion sources, or dark web crawlers.

Role**: Digital : Data Science Required Technical Skill Set: Digital : Data Science Desired Experience Range: 03 - 08 yrs Notice Period: Immediate to 90Days only Location of Requirement: Hyderabad/Bangalore/Pune/Chennai/Kolkata We are currently planning to do a Virtual Interview Job Description: Must-Have** (Ideally should not be more than 3-5) Proficiency in Python or R for data analysis and modeling. Strong understanding of machine learning algorithms (regression, classification, clustering, etc.). Experience with SQL and working with relational databases. Hands-on experience with data wrangling, feature engineering, and model evaluation techniques. Experience with data visualization tools like Tableau, Power BI, or matplotlib/seaborn. Strong understanding of statistics and probability. Ability to translate business problems into analytical solutions. Good-to-Have Experience with deep learning frameworks (TensorFlow, Keras, PyTorch). Knowledge of big data platforms (Spark, Hadoop, Databricks). Experience deploying models using MLflow, Docker, or cloud platforms (AWS, Azure, GCP). Familiarity with NLP, computer vision, or time series forecasting. Exposure to MLOps practices for model lifecycle management. Understanding of data privacy and governance concepts. SN Responsibility of / Expectations from the Role 1 Work with stakeholders to identify business requirements and opportunities for leveraging data. Design and implement advanced analytics models using machine learning and statistical techniques. Clean, process, and analyze large datasets from various sources (structured & unstructured). Develop, test, and deploy predictive models and data pipelines. Create data visualizations, dashboards, and reports to communicate insights to non-technical users. Collaborate with data engineers, analysts, and product teams to integrate models into production environments. Monitor and continuously improve model performance. Stay up-to-date with latest research, tools, and techniques in data science and AI.