Role Overview
Michael Page is recruiting for an ML Engineer on behalf of a venture-backed healthcare AI client in Bangalore, Karnataka, India. In this technical role, you will design, build, and deploy production-oriented Natural Language Processing (NLP) and Large Language Model (LLM) architectures tailored for oncology workflows within electronic health record (EHR) environments. The position focuses on clinical information extraction, building high-performance Retrieval-Augmented Generation (RAG) pipelines, model fine-tuning, and developing evaluation frameworks to accelerate clinical trial matching, medical data abstraction, and oncology research operations.
Core Responsibilities
- NLP & LLM Architecture: Design, develop, and deploy NLP models and LLM solutions purpose-built for clinical applications and healthcare documentation.
- Document Understanding & Extraction: Build automated clinical information extraction and document-understanding pipelines to convert unstructured patient records into standardized data schemas.
- RAG Pipelines & Fine-Tuning: Architect and test Retrieval-Augmented Generation (RAG) frameworks, design structured prompt templates, and execute model fine-tuning experiments.
- Benchmarking & Error Analysis: Develop comprehensive evaluation, benchmarking, and error-analysis tools tracking precision, recall, and F1 metrics across clinical edge cases.
- Data Quality Collaboration: Partner with clinical AI specialists to optimize data labeling, annotation guidelines, and dataset quality for domain-specific models.
- Production-Grade Engineering: Write modular, maintainable, and high-performance Python code to deploy and monitor models in production environments.
Qualifications & Requirements
- Educational Background: B.Tech or equivalent degree from a Tier-1 engineering institution (IITs, NITs, BITS) in Computer Science, Data Science, AI, or a related discipline.
- Professional Experience: 1.5 to 4 years of dedicated technical experience in machine learning, NLP, LLMs, or data-intensive software engineering.
- Core Programming: Advanced software engineering capabilities in Python with an emphasis on production-ready design patterns.
- Machine Learning Tooling: Hands-on technical proficiency with PyTorch, Hugging Face libraries, Transformers, and vector embeddings.
- Applied AI Techniques: Demonstrated experience implementing prompt engineering strategies, RAG frameworks, model fine-tuning, and statistical experiment design.
- Real-World Data Processing: Proven ability to preprocess, clean, and extract value from noisy, unstructured real-world datasets and complex domain data.
About the Organization
Michael Page is a leading global professional recruitment consultancy operating across worldwide markets. This placement represents an investor-backed healthcare technology client that collaborates with top cancer centres to transform oncology care and research operations through cutting-edge artificial intelligence.