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Remote role and mid-level seniority raise applicant density, but niche GenAI/LLM skills limit competition.
Deep GenAI/LLM expertise and healthcare compliance knowledge reduce cross-industry transferability, so sensitivity is high.
Explicit 6+ years plus mandatory GenAI, LLM, vector DB and MLOps tech stack implies high strictness.
Design, build, train, and deploy advanced AI and Generative AI solutions including ML, DL, NLP, and image processing models for healthcare applications.
Develop, test, and maintain AI solutions ensuring reliability, scalability, compliance with healthcare regulations, and integration with existing technology stacks.
Perform data preprocessing, feature engineering, AI model optimization, continuous monitoring, and ensure security and ethical AI implementation in healthcare technology platforms.
Bachelor's or Master's or higher degree in Computer Science, AI, Data Science, Engineering, or related field.
6+ years of experience in AI/ML engineering focusing on AI solution development and deployment.
Proficient in Python, TensorFlow, PyTorch, and experienced in LLM fine tuning, Gen AI with RAG architecture, Lang Chain, Lang Graph, and Vector/Graph databases.
Experience with cloud platforms (AWS, Azure, or GCP), MLOps, big data technologies (Spark, Hadoop, SQL, NoSQL), and front end development with Streamlit is mandatory.
Experienced in building, optimizing, and deploying complex AI/Gen AI models specifically for healthcare applications with regulatory compliance knowledge (HIPAA, CMS).
Proven ability to lead teams, translate business requirements into feasible AI solutions, and communicate effectively with multiple stakeholders.
Hands-on experience with Agentic AI frameworks, multi-modal LLMs, prompt engineering, and implementing AI security guardrails in operational environments.