Responsibilities
- Strong expertise in Python programming and one of the Deep Learning frameworks (PyTorch, MXNet, TensorFlow, Keras) and understanding of LLMs, LLMOps and Generative AI - to be able to deliver per specifications; complete assignments without assitance by exercising judgment & appropriate actions
- Knowledge of Classification, Prediction, Recommender Systems, Time Series Forecasting, Anomaly Detection, Optimization, Graph ML, NLP. Hands-on develop ML models using the above techniques
- Ability to both use existing libraries (ML, Deep Learning, Re-inforcement Learning) as well as design algorithms ground-up; Able to prepare data pipelines and feature engineering pipelines to build robust models
- Combine ML Sciences depth, programming expertise and mathematical understanding of techniques to deliver state-of-the-art ML solutions for problem solving across Healthcare domain
- Drives selction of methods and techniques to drive solutions
- Demonstrate strong program management to be able to multi-task effectively
- Be able to mentor & lead junior data scientists effectively
- Contribute to peer reviews, team learning, meeting product objectives and develop best practices for the organization
- Strong experience in LLM Systems and LLMOps. Prior experience with Prompt Engineering and RAG systems