CVS Health is committed to delivering better health outcomes through innovative solutions. The Staff Machine Learning Engineer will play a key role in designing and developing AI-powered healthcare solutions, focusing on generative AI and full-stack applications.
Responsibilities:
- Partner with stakeholders to identify, evaluate, document, and shape GenAI use cases (copilots, automation, decision support, and insight generation) with clear success metrics
- Design solution architectures that integrate LLMs with enterprise systems, data sources, and tool/function calling while meeting latency and reliability expectations
- Develop prototypes rapidly and validate them through evaluation, red-teaming, and user feedback; document tradeoffs and recommendations
- Build production-grade services and full-stack experiences (APIs, UIs, workflows) with secure authentication/authorization, audit logging, and scalable deployment patterns
- Implement safety, privacy, and compliance controls (e.g., PHI/PII protection, prompt injection defenses, data residency constraints, and policy-based filtering)
- Instrument solutions end-to-end with metrics, traces, logs, and model/app observability; contribute to SLOs, error budgets, and operational runbooks
- Build and maintain evaluation harnesses for LLM quality, safety, and business outcomes (offline tests, golden sets, regression suites, and online experiments)
- Implement RAG pipelines (chunking, embedding, vector search, reranking) and optimize for accuracy, cost, and latency
- Collaborate with platform teams on deployment, monitoring, drift/quality detection, and incident response for model-backed services
- Contribute reusable libraries and patterns for prompt management, retrieval, tool calling, and policy enforcement
- Participate in design reviews and code reviews; mentor senior and mid-level engineers on GenAI engineering practices
- Continuously improve developer experience through templates, CI/CD automation, and documentation that accelerates safe adoption
Requirements:
- 7+ years of software engineering supporting Data or AI/ML initiatives, including building and operating production services
- 3+ years applying ML/AI in production; demonstrated hands-on GenAI delivery (LLMs, RAG, evaluation, and safety controls)
- 3+ years of experience delivering solutions in high-scale, high-availability environments with strong security and compliance requirements
- Bachelor's degree or equivalent experience (High School Diploma and 4 years relevant experience)
- Strong full-stack engineering skills (backend services, APIs, and modern web application development) with a focus on reliability and security
- Hands-on expertise with LLM application patterns: RAG, tool/function calling, prompt management, evaluation, and guardrails
- Experience with Python and at least one additional backend language; familiarity with common ML libraries and serving frameworks
- Working knowledge of containerization and Kubernetes, CI/CD, infrastructure-as-code concepts, and production observability
- Ability to communicate clearly, influence across teams, and translate business needs into implementable technical plans