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Remote role, metro locations, and mid-level experience amplify applicant competition.
Requires specialized GenAI/LLM and healthcare compliance experience, limiting cross-industry transferability.
Explicit 5+ years requirement plus specialized GenAI, LLM, vector DB and MLOps skills increases strictness.
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Design, develop, and deploy advanced AI and Generative AI (Gen AI) solutions including multi-modal LLMs, NLP, computer vision, and predictive models for healthcare applications.
Lead end-to-end AI solution deployment and integration in cloud and on-premises environments, ensuring compliance with healthcare regulations and continuous performance monitoring using ML Ops and LLM Ops.
Collaborate across teams to translate business requirements into operational AI-driven workflows and solutions, including automation enhancements and security implementation in Gen AI frameworks.
Bachelor’s or Master’s degree in Computer Science, AI, Data Science, Engineering or related field.
5 to 15 years of experience in AI/ML engineering focused on development and deployment of AI solutions.
Hands-on expertise in machine learning, deep learning, Gen AI (multi modal LLMs), NLP, computer vision, and experience fine-tuning LLMs like GPT or similar.
Proficiency in Python, TensorFlow, PyTorch, cloud platforms (AWS/Azure/GCP), MLOps, big data technologies (Spark, Hadoop, SQL, NoSQL).
Experienced in building complex AI solutions using advanced Gen AI architectures including RAG, Agentic AI, Lang Chain, Lang Graph, and vector/graph databases.
Capable of leading teams and cross-functional collaboration, translating healthcare business needs into scalable AI implementations under regulatory compliance.
Strong practical skills in AI solution deployment with expertise in workflow automation, security guard rails, model optimization, and front-end tools such as Streamlit.