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Mid-level popular AI role, metro Bangalore location, and broad LLM/multimodal requirements increase applicant competition.
Requires healthcare domain experience, HIPAA/GDPR knowledge, and EHR exposure, making background fit highly sensitive.
Mandatory 2+ years, healthcare/EHR experience, and specialized LLM and compliance skills create high shortlisting strictness.
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Develop, fine-tune, and deploy large language models (LLMs) and multimodal AI systems for healthcare applications focusing on clinical and operational integration.
Lead end-to-end AI lifecycle activities including data processing, model training, optimization, evaluation, and deployment into production healthcare products.
Implement and maintain AI infrastructure including voice assistant applications, continuous learning workflows, and adhere to healthcare data privacy and compliance requirements.
Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or related field.
Minimum 2 years of hands-on experience in end-to-end AI/ML development lifecycle, specifically in a healthcare provider setting with exposure to EHRs or healthcare data domains.
Proficient in Python and ML frameworks such as PyTorch or TensorFlow with demonstrated experience in training/fine-tuning LLMs and speech processing models (STT/TTS).
Experience working with healthcare datasets in production pipelines ensuring data privacy compliance (HIPAA, GDPR) and healthcare-specific AI algorithm development.
Experienced AI engineer capable of delivering production-ready AI solutions specifically in provider healthcare environments with clinical data integration expertise.
Practitioner skilled in applying modern NLP/NLU, foundation model customization, prompt engineering, and speech-to-text/text-to-speech integration for conversational AI.
Able to work in agile, cross-functional teams producing scalable, compliant, and reliable AI systems with strong attention to reproducibility, safety, and continuous improvement.