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Tier-1 brand, mid-level ML role, metro location, and broad desirable ML/LLM skills generate high competition.
Specialized ML, LLM, and production-scale AI skills make industry transferability limited, so sensitivity is high.
Explicit senior experience, advanced degree, and specific ML/LLM production skills imply high shortlisting strictness.
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Design, develop, and implement production-grade AI/ML systems incorporating LLM models and Retrieval-Augmented Generation (RAG) to solve large-scale business problems.
Build and enhance AI processing pipelines with focus on throughput, accuracy, resilience, and maintainability using frameworks like LangGraph and Google ADK.
Collaborate cross-functionally to deliver scalable and tailored AI solutions by testing model performance, customizing for use cases, and conducting data modeling experiments.
Advanced Degree in Computer Science, Data Science, or equivalent discipline.
At least 6 years of industry experience with 4+ years as hands-on ML Engineer/Data Engineer/Data Scientist.
Proficiency in Python, FastAPI, deep learning frameworks, and experience building scalable distributed ML models in production.
Experience with analytics tools (SQL, Python, AWS suite) and machine learning techniques like regression, classification, clustering, causal inference.
Experienced in end-to-end project delivery in senior data scientist/engineer roles, especially involving large scale ML system design.
Strong expertise in LLMs, prompt engineering, and RAG pipeline development for tailored AI solutions.
Familiar with cloud-based ML services, particularly AWS ML ecosystem (e.g. Sagemaker), and frameworks like TensorFlow or PyTorch leveraging GPUs.