Top AI & Machine Learning Jobs

Research and develop LLM and NLP solutions (including agentic AI) for healthcare, collaborate with RUAI and engineering teams, build MLOps pipelines, document code and models, publish/patent novel methods, and ensure solutions comply with company AI policies.

Lead strategy and execution of enterprise-scale AI/ML and generative AI solutions for claims, eligibility, and benefits. Define AI engineering roadmap, build LLM and agentic systems, scale cloud-native AI workloads, enforce responsible AI governance, partner with product and business stakeholders, manage budgets, and hire and mentor a global engineering organization to deliver measurable business outcomes.

Design, develop and deploy AI products on Azure and Optum AI platforms using Python, Java/Spring and React. Support production deployments, and work with Oracle/MySQL databases while following company policies and procedures.

Design, build, and deploy production-grade AI/ML and LLM solutions for claims processing, eligibility, prior authorization, and payment integrity. Build scalable data pipelines, integrate models with core payer systems, ensure HIPAA/PHI-safe pipelines and Responsible AI governance, monitor and retrain models, and partner with cross-functional teams to deliver reliable, CI/CD-driven solutions.

Lead product strategy and roadmaps for data science, ML, and cloud products in healthcare. Translate business needs into technical requirements and user stories, drive Agile delivery, analyze user and market data to set metrics, design and deploy AI-powered solutions responsibly, mentor junior PMs, and ensure compliance with healthcare regulations throughout the product lifecycle.

Lead end-to-end product lifecycle for healthcare-focused data science, cloud, and analytics products. Define strategy, prioritize backlog, translate business needs into technical requirements, collaborate with engineering and data science to design and deploy AI/ML solutions, support launches, and measure product performance.

Design, build, and productionize AI systems (genAI, agents, RAG) with observability, model quality, governance, and responsible-AI controls. Implement serving/inference, cloud deployments, model registry/experiment tracking and cross-functional leadership to scale claim-edit automation and agentic workflows.

Individual contributor lead role to architect, build, and deploy agentic LLM systems, RAG/hybrid search, and scalable microservices on cloud/Big Data platforms. Owns MLOps/LLMOps, evaluation frameworks, HIPAA-compliant security controls, and integrations with data and internal AI platforms. Partners with data engineering, mentors engineers, prototypes POCs, and drives production reliability and cost KPIs.

Design and build production-grade GenAI solutions: RAG pipelines, agentic multi-agent workflows, knowledge-base chatbots, vector DBs, LLM integrations, observability, PII redaction, and deploy AI backends with monitoring and documentation.

The Principal Data Scientist will lead AI system development in healthcare, overseeing LLM implementation, model lifecycle, and compliance with regulations, while ensuring operational excellence and technical influence across teams.