| Job Title | Lead Data Scientist / Lead AI Engineer GenAI & Advanced ML |
|---|---|
| Category | Engineering |
| Location | Pune, Mumbai (All Areas) |
| Company | Go Digital Technology Consulting |
| Description | Job description Job Role: Lead AI Engineer GenAI & Advanced ML Location: Mumbai / Pune Job Type: Full-time Experience: 5 to 8years About the Role We are looking for a Lead AI Engineer Generative AI with leadership experience and deep expertise in AI/ML and production-grade GenAI systems. This role requires a hands-on technical leader who has built, deployed, and scaled Generative AI solutions while leading teams and driving architectural decisions. The ideal candidate will have a strong foundation in machine learning, deep learning, and statistical modeling, along with real-world experience in LLMs, RAG, fine-tuning, and AI agents. A background in forecasting or predictive modeling should complement broader AI/ML problem-solving. Strong hands-on experience with AWS (especially Bedrock and SageMaker) is mandatory. If you enjoy owning GenAI strategy end-to-end and building scalable AI systems, this role is for you. Key Responsibilities Lead the design, development, and deployment of AI/ML and Generative AI solutions. Architect end-to-end GenAI systems including data pipelines, training, evaluation, deployment, and monitoring. Drive initiatives across: LLM-based applications Retrieval-Augmented Generation (RAG) Prompt engineering & optimization Fine-tuning & model adaptation AI agents & orchestration workflows Build and deploy GenAI solutions on AWS Bedrock and SageMaker. Apply ML/DL techniques for forecasting, prediction, and intelligent automation. Lead and mentor AI engineers and data scientists. Collaborate with product and business stakeholders to deliver scalable AI solutions. Design and maintain ML/GenAI pipelines for experimentation and retraining. Ensure responsible AI, scalability, and performance standards. Qualifications & Skills 58 years of experience in AI/ML, Data Science, or AI Engineering, with 1–2 years in a lead role. Strong foundation in Machine Learning, Deep Learning, and Statistical Modeling. Generative AI (Hands-on): LLMs and foundation models Prompt engineering RAG pipelines & vector databases Fine-tuning & inference optimization AI agents / orchestration AWS (Mandatory): Amazon Bedrock Amazon SageMaker Experience deploying AI/ML solutions on AWS Proficiency in Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow). SQL and large-scale data processing experience. Strong understanding of ML system design and model evaluation. Excellent communication and stakeholder management skills. Preferred Qualifications MLOps practices (CI/CD, monitoring, versioning). Experience with Spark / big data ecosystems. Knowledge of vector databases (FAISS, Pinecone, Weaviate). Exposure to AI governance and responsible AI frameworks. |
| Salary | Not Disclosed |
| Last Date | 2026-04-30 00:00:00 |
| Apply Link | Click Here |
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