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Strong Tier-1 brand, mid-level ML role, metro hiring, and broad GenAI requirements drive high competition.
Core ML skills transfer across industries but healthcare domain knowledge increases fit sensitivity.
Multiple explicit years requirements and mandatory deep learning/GenAI skills make screening highly selective.
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Design and develop advanced NLP, ML, and AI products focused on healthcare applications, including modeling in NLP, NLU, NLG, and time series forecasting.
Lead end-to-end machine learning lifecycle from data ingestion, feature engineering, modeling to deployment and performance tracking across multiple products.
Run complex proof-of-concepts and manage prioritization and technical work for building scalable AI/ML solutions including GenAI model optimization and agentic AI implementations.
Master's degree in Computer Science, Statistics, Electrical/Electronic Engineering, or other quantitative field with 4+ years industry experience OR PhD with 2+ years industry experience in data science, machine learning or related field.
At least 4 years of experience with Deep Learning frameworks and distributed training, 3+ years in machine learning and deep learning modeling.
Minimum 1.5 years experience in Generative AI (GenAI) model optimization and 1+ year in Agentic AI.
Excellent communication, writing, and presentation skills.
Experienced practitioner comfortable leading full-cycle AI/ML projects with autonomy, especially in healthcare domain technologies like NLP and GenAI.
Strategic thinker adept at decomposing complex AI problems into practical solutions, influencing design decisions and best practices.
Able to mentor scientists and lead scalable deployment of AI solutions from conceptualization through successful delivery.