Machine Learning Engineer

CVS Health•Wellesley, MA

1d•$86,520 - $173,040

About The Position

CVS Health is seeking a versatile Machine Learning Engineer who can work across backend platform engineering, full-stack AI application development, and Generative AI as team priorities change. The role builds and maintains production backend services and APIs for large-scale audience segmentation and activation, and develops Generative AI and agentic applications, including LLM orchestration, retrieval-augmented generation (RAG), and evaluation. The engineer contributes across backend services and user interfaces to deliver complete AI products, collaborates with platform and network security teams on cloud infrastructure and access management, and helps keep deployed systems healthy. The role works with product, data science, engineering, and business stakeholders to turn business needs into technical solutions. The position is full-time, with 40 anticipated weekly hours. The typical pay range is $86,520 to $173,040, with eligibility for a CVS Health bonus, commission, or short-term incentive program. The position is eligible for benefits including medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility. The application window is anticipated to close on November 29, 2026.

Requirements

At least 2 years building, deploying, and maintaining 0-to-1 production ML or data-intensive systems as an MLE or SDE, or a PhD with a relevant technical internship.
Strong Python and SQL skills.
Experience building RESTful APIs, such as with FastAPI, and integrating third-party services.
Solid software engineering practices, including CI/CD, containerization, automated testing, and cloud deployment.
Strong curiosity, self-direction, and willingness to challenge the status quo.
Excellent communication and collaboration skills across cross-functional teams, including product, data science, engineering, marketing, and operations stakeholders.
Master’s degree in Computer Science, Statistics, Engineering, or a related field, or equivalent work experience.

Nice To Haves

Experience with direct-to-consumer (D2C) platforms and individual personalization.
Hands-on experience with agentic workflows, LLM frameworks such as LangChain or LangGraph, RAG, vector search, and MCP servers.
Experience with Google Cloud Platform (GCP), especially BigQuery and Vertex AI.
Front-end development experience in React, CSS, and TypeScript, preferably in more than one.
Background in AdTech, MarTech, recommendation systems, and experimentation workbench.
PhD preferred.

Responsibilities

Build and maintain production backend services, APIs, and integrations for large-scale audience segmentation and activation.
Develop and deploy Generative AI and agentic applications, including LLM orchestration, retrieval-augmented generation (RAG), and evaluation.
Contribute across the full stack, from backend services to user interfaces, to deliver complete AI products.
Collaborate with platform and network security teams on cloud infrastructure, secure networking, and access management.
Maintain deployed systems through CI/CD, testing, monitoring, and incident triage.
Work with product, data science, engineering, and business stakeholders to turn business needs into technical solutions.