Director - I - ML Engineering

Internal Company: Tata Digital Private Limited About Us Tata Digital is a future-ready company that focuses on creating consumer-centric, high-engagement digital products. By creating a holistic presence across various touchpoints, we aim to be the trusted partner of every consumer and delight them by powering a rewarding life. The company's debut offering, Tata Neu is a super- app that provides an integrated rewards experience across various consumer categories like groceries, fashion and electronics, travel and hospitality, health and fitness, entertainment, and financial services on a single platform. Founded in March 2019, Tata Digital Private Limited is a wholly owned subsidiary of Tata Sons Private Limited. Basic Information • Role Title: Dir- AI/ML • Required Technical Skillset: Python, Java/Scala/Golang, ML frameworks at least one (TensorFlow/PyTorch), MLOps, Microservices, Cloud at least one (Azure/AWS/GCP), LLM/Generative AI • Work Location: Gurugram • Work Experience: 12-15 years About the Team and Role The AI Engineering and Solutions team at Tata Digital is responsible for building and deploying next-generation AL Platform and intelligence data solutions across various consumer products and services on the Tata Neu platform. We engage closely with cross-functional teams—Product, Engineering, Marketing, Data Science, Customer Experience, and more—to drive data-informed strategies and deliver cutting-edge ML Platform advance data capabilities including Generative AI and LLM (Large Language Model) solutions for customer-facing applications. We are seeking an Engineering Manager – AI & LLM with 12–15 years of overall experience, including hands-on development and leadership in Product, AI/ML engineering. In this role, you will lead a team of skilled engineers and collaborate closely with data scientists, product managers, and other stakeholders to build scalable AI platforms, develop advanced LLM-based solutions, and integrate MLOps best practices. Key Responsibilities: Team Management & Engineering Practices • Lead a team of AI/ML engineers; set goals, conduct reviews, and foster best practices. • Enforce best practices in coding, design reviews, and software craftsmanship. • Foster a collaborative environment with clear career paths and Promote continuous learning in MLOps, microservices, and advanced AI/LLM development. AI & Data Platform Architecture • Design scalable AI/ML platforms, Gen AI infra and related solutions • Collaborate with data engineering for real-time/batch processing and smooth product integration. MLOps & Microservices • Implement MLOps (MLflow, Kubeflow) for streamlined model development and monitoring. • Architect microservices (Docker, Kubernetes) with CI/CD for low-latency, high-throughput AI services. LLM & Generative AI Solutions • Develop solutions using LLMs (GPT, etc.), prompt engineering, RAG, and fine-tuning. • Leverage multi-modal embeddings, vector databases, and semantic search in collaboration with Data Science. Performance & Scalability Internal • Optimize for low-latency inference, high-volume traffic, caching, load balancing, and auto-scaling. • Implement monitoring and alerting to maintain SLAs and detect model drift. Product & Business Enablement • Align AI/ML roadmaps with strategic objectives; translate technical solutions into measurable outcomes. • Drive AI/LLM adoption across business units for new use cases and revenue growth. Cross-Functional Collaboration • Partner with Engineering, Product, Marketing, and Data Science to integrate AI solutions across Tata Neu. • Coordinate with security, compliance, and infrastructure teams to meet enterprise standards. Competencies for the Role 1. Educational Background o B.Tech/BE/M.Tech or equivalent in Computer Science, Data Science, or a related field. 2. Technical Expertise o Programming: Expert in Python and at least one of Java/Scala/Golang for building robust microservices. o ML & LLM Frameworks: Hands-on experience with TensorFlow, PyTorch, or Scikit-learn; familiarity with LLM fine-tuning and associated libraries (e.g., Hugging Face). o Cloud & DevOps: Proficiency in cloud platforms (Azure/AWS/GCP) and container orchestration (Kubernetes, Docker). o Data Processing: Familiarity with Spark/Kafka or similar technologies for large-scale or real-time data workflows. o Generative AI, Agents and RAG: 1. Experience of building applications with LangChain, LangGraph, LlamaIndex and similar frameworks and libraries. 2. Exposure to Vector Databases, Embedding Models, and Semantic Similarity Search. 3. Expertise in advanced Prompt Engineering and Retrieval Augmented Generation (RAG) techniques for working with structured and unstructured data. 4. Experience in applying AI to practical and comprehensive technology solutions, and developing and deploying machine learning systems into production. 3. MLOps & Automation o Experience in setting up CI/CD pipelines, model registries, and feature stores. o Knowledge of best practices for model monitoring, logging, and drift detection. 4. Analytical & Problem-Solving Skills o Ability to design experiments, interpret complex data, and create actionable insights. o Familiarity with advanced statistical and ML techniques, including advanced NLP, LLM fine-tuning, and agent-based AI. 5. Product & Business Acumen o Proven track record of delivering Data & ML solutions that impact business metrics and user experience. o Capable of balancing technical trade-offs with product requirements and ROI considerations. 6. Communication & Leadership o Strong written and verbal communication skills for stakeholder alignment. o Demonstrated ability to lead projects and mentor cross-functional teams. Want to know more about us? https://www.tata.com/business/tata-digital/tata-neu https://www.tata.com/newsroom/business/tata-neu https://www.linkedin.com/company/tata-digital/about/ https://www.youtube.com/watch?v=xw-l5jBWWpI