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Staff Machine Learning Engineer - Generative AI & Full-Stack Applications
- Saint Paul, Illinois, United States
- Saint Paul, Illinois, United States
Über
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.
Benefits We take pride in offering a comprehensive and competitive mix of pay and benefits that reflects our commitment to our 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.
EEO Statement Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.
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Sprachkenntnisse
- English
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