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Staff Machine Learning Engineer - Generative AI & Full-Stack Applications
CVS HealthUnited StatesWe’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who c
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Staff Machine Learning Engineer - Generative AI & Full-Stack Applications
- United States
- United States
À propos
At CVS Health, our purpose is to deliver better health outcomes by meeting consumers where they are—through local care, digital experiences, and a nationwide team committed to quality, safety, and affordability.
Our Solutions Engineering and Infrastructure organization is building an enterprise AI/ML capability that delivers reliable, responsible, and secure AI-powered platforms and solutions at Fortune 5 scale, and this role is foundational to help us develop that capability.
This is a senior individual-contributor role, focused on identifying evaluating and documenting high-value use cases, designing and prototyping AI-powered solutions, and evolving them into secure, resilient, enterprise-ready products and platform components.
Key Responsibilities:
AI Solution Design & Prototyping
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.
Production Engineering & Enterprise Readiness
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.
Model Enablement & Evaluation
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.
Reusable Components & Engineering Excellence
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.
Required Qualifications:
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.
Preferred Qualifications
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.
Education:
Bachelor’s degree or equivalent experience (High School Diploma and 4 years relevant experience)
Pay Range
The typical pay range for this role is:
$106,605.00 - $284,280.00
This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above. This position also includes an award target in the company’s equity award program.
Our people fuel our future. Our teams reflect the customers, patients, members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our colleagues and their families.
This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.
Additional details about available benefits are provided during the application process and on Benefits Moments (https://learn.bswift.com/cvshealth-mainland) .
We anticipate the application window for this opening will close on: 07/08/2026
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
CVS Health is an equal opportunity/affirmative action employer, including Disability/Protected Veteran — committed to diversity in the workplace.
Compétences linguistiques
- English
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