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Prestigious biotech AI brand, Bangalore metro, mid-level ML role and broad LLM skillset increase competition.
Strong ML skills transferable, but healthcare-specific HIPAA and clinical data requirements moderately limit cross-industry fit.
Explicit 1–3 years, mandatory ML/LLM experience, specific frameworks, and healthcare data compliance demands strict filters.
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Develop and deploy machine learning and deep learning models focused on NLP and Large Language Model (LLM) applications for healthcare use cases.
Prepare and preprocess healthcare data, perform feature engineering and model evaluation with appropriate metrics, and implement LLM components such as embedding pipelines and prompt-based systems.
Build and maintain model inference components (e.g., REST APIs, batch pipelines), ensure code quality with version control and Docker containerization, and comply with healthcare data privacy and governance standards (HIPAA).
Bachelor’s or Master’s degree in Computer Science, Data Science, or related field.
1 - 3 years of experience in data science, machine learning, or applied AI roles.
Strong proficiency in Python and deep learning frameworks like PyTorch, TensorFlow, or scikit-learn.
Experience with NLP concepts including transformers and LLM fundamentals; familiarity with building production components including REST APIs, Docker, Git, and awareness of healthcare data privacy concerns such as HIPAA.
Experienced in NLP and LLM workflows particularly in healthcare or biomedical domains, capable of handling unstructured healthcare data.
Comfortable working in hybrid environments collaborating with engineering and product teams, maintaining software engineering best practices including modular code and containerization.
Detail-oriented in debugging and optimizing models and inference systems while ensuring compliance with healthcare data governance.