Staff Machine Learning Engineer

We’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 care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary: Design, build, and operationalize scalable, secure, and responsible Generative AI solutions across the affiliate line of business. In this role, you will work across AWS Bedrock, GCP Vertex AI, serverless compute, event‑driven architectures, vector search, and agentic frameworks to deliver AI systems that accelerate business outcomes and improve experiences for our members, providers, and colleagues. This role blends hands-on engineering with architecture, platform leadership, and cross‑functional collaboration in a HIPAA‑regulated environment. What you will do Drives the development and implementation of advanced machine learning models and algorithms to solve complex healthcare problems, leveraging techniques such as predictive modeling, deep learning, and natural language processing. Collaborates with multiple departments, including data scientists, clinicians, and Information Technology (IT) professionals, to understand business requirements, define machine learning projects, and prioritize initiatives based on strategic objectives. Interfaces with stakeholders to define performance metrics and evaluation methodologies for machine learning models, contributing to rigorous testing, validation, and performance monitoring of models to ensure accuracy and reliability. Designs and implements scalable and efficient machine learning systems, including data pipelines, preprocessing, feature engineering, and model training, ensuring the quality and integrity of healthcare data used for analysis. Advises on the optimization and improvement of data pipelines, model training processes, and infrastructure to enhance efficiency, scalability, and performance of machine learning solutions. Consults on and presents technical findings, insights, and recommendations to both technical and non-technical stakeholders, contributing to the dissemination and application of machine learning insights in the healthcare industry. Ensures compliance with data privacy regulations, ethical guidelines, and industry standards in machine learning engineering, supporting the development of protocols and practices for model interpretability, fairness, and transparency. Manages team performance through regular, timely feedback as well as the formal performance review process to ensure delivery of exceptional services and engagement, motivation, and team development. Stays up-to-date with the latest advancements in machine learning and related technologies, continuously exploring and evaluating new algorithms and methodologies to enhance machine learning capabilities in healthcare applications. AI & Cloud Engineering Design, build, and deploy production-grade LLM and GenAI applications using the full breadth of AWS Bedrock and GCP Vertex AI capabilities (models, tuning, pipelines, vector search, guardrails, evaluation). Build cloud-native AI systems using: • Serverless architectures (AWS Lambda, Step Functions, EventBridge; Cloud Functions, Cloud Run) • Event-driven architectures (SNS/SQS, Pub/Sub, EventBridge, triggers) • Microservices and APIs (Node.js, Java, Python) Agentic Frameworks & Automation Architect agentic AI systems using Bedrock Agents, Vertex AI Agent Builder, or approved frameworks (LangGraph, LangChain, LlamaIndex Agents). Deliver multi-step reasoning, tool-use, and workflow orchestration for enterprise use cases. Comfortable designing and developing AI Agents using Copilot Studio and Cloud flow (Power Automate). RAG Architectures Develop robust Retrieval-Augmented Generation (RAG) systems using Bedrock Knowledge Bases, Vertex AI Vector Search, or custom vector databases (OpenSearch, Pinecone, FAISS, pgvector). Design document ingestion, embedding, chunking, grounding, and retrieval pipelines that integrate securely with enterprise data. Model Lifecycle & Operationalization Lead model experimentation, fine‑tuning, evaluation, deployment, and monitoring across cloud platforms. Optimize cost, performance, token usage, latency, and scaling for production workloads. Responsible AI & Compliance Ensure all solutions meet CVS Health’s Responsible AI standards, including model documentation, governance, risk assessment, and auditability. Design systems that adhere to HIPAA, data privacy, and security requirements. Collaboration & Technical Leadership Partner with product, engineering, data, security, and compliance teams to shape roadmaps and solution direction. Mentor engineers and contribute reusable patterns, frameworks, and platform accelerators. Required Qualifications: 8+ years in large-scale software development 5+ years solution architecture or system design experience. 5+ years building large-scale microservices/APIs using Node.js. 3+ years hands‑on experience with GCP and AWS (serverless, event-driven, AI/ML, CI/CD). AWS Bedrock (any combination of models, agents, knowledge bases, guardrails, tuning, evaluation) or GCP Vertex AI (Model Garden, Extensions/Agents, Vector Search, Pipelines, Tuning) or similar technologies. Strong communication and leadership skills. Strong experience with Python for AI/ML engineering. Production experience with: Agentic AI frameworks RAG architectures and vector databases Serverless and event-driven designs Preferred Qualifications: Experience with Vertex AI’s Generative AI Studio, vector search orchestration, and agent capabilities. Hands-on experience with vector databases (OpenSearch, Pinecone, FAISS, pgvector, Milvus). Strong knowledge of prompt engineering, evaluation, observability, and LLM security patterns. Ability to write clear design docs, architectural diagrams, runbooks, and technical briefs. Agile/SAFe experience in large enterprises. Cloud certifications (AWS/GCP) preferred. Education: Bachelor’s Degree in Computer Science or a related field, or equivalent experience. Pay Range The typical pay range for this role is: $106,605.00 - $260,590.00 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. We anticipate the application window for this opening will close on: 09/28/2026 Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws. Our Work Experience is the combination of everything that's unique about us: our culture, our core values, our company meetings, our commitment to sustainability, our recognition programs, but most importantly, it's our people. Our employees are self-disciplined, hard working, curious, trustworthy, humble, and truthful. They make choices according to what is best for the team, they live for opportunities to collaborate and make a difference, and they make us the #1 Top Workplace in the area.