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Remote role, metro Bangalore location, and in-demand ML/GenAI skills produce moderate applicant competition.
Core ML/GenAI skills are transferable, but healthcare compliance preference raises sensitivity to medium.
Explicit years plus mandatory AI/LLM, MLOps, and deployment skills create high shortlisting strictness.
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Design, build, train, and deploy AI and Generative AI solutions (multi modal LLMs, NLP, computer vision) tailored for healthcare applications focusing on improving outcomes and efficiency.
Develop and optimize AI models including fine-tuning LLMs using various techniques and architectures like RAG, Lang Chain, Lang Graph, and Agentic AI frameworks with end-to-end deployment on cloud and on-premises.
Ensure integration of AI solutions with existing systems via API development, oversee data processing compliant with healthcare regulations (HIPAA), and maintain continuous model performance and security monitoring.
Bachelor’s or Master’s degree or higher in Computer Science, AI, Data Science, Engineering, or related field.
2+ years to around 15 years of professional experience in AI/ML engineering focused on developing and deploying AI solutions.
Proficient in Python, TensorFlow, PyTorch, AI frameworks; experienced with multi modal LLMs, prompt engineering, model optimization, inference efficiency.
Familiarity with cloud platforms (AWS, Azure, GCP), ML Ops/LLM Ops, big data technologies (Spark, Hadoop, SQL, NoSQL).
Experienced in healthcare-related AI applications with knowledge of regulatory compliance such as HIPAA and CMS.
Strong expertise in advanced AI technologies including multiple LLM fine-tuning techniques, Gen AI architectures (RAG, Agentic AI), and related frameworks (Lang Chain, Lang Graph).
Capable of translating complex business challenges into AI-driven solutions and collaborating across stakeholders for system integration and deployment in a healthcare technology domain.