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At CVS Health, we’re building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care.

As the nation’s leading health solutions company, we reach millions of Americans through our local presence, digital channels and more than 300,000 purpose-driven colleagues – caring for people where, when and how they choose in a way that is uniquely more connected, more convenient and more compassionate. And we do it all with heart, each and every day.

POSITION SUMMARY

Cyber Defense within CVS Health is seeking a well experienced Staff Machine Learning Engineer to join and technically lead our growing team. Staff Machine Learning Engineer will be responsible for developing and deploying security specific machine learning solutions following CVS Health specific business and technology requirements. Additionally, this Staff Machine Learning Engineer will help to define, drive and deliver all aspects of the data science product development lifecycle, from solution architecting, programming, testing, implementation, delivery of data science analytics products.

_What We Expect of You:_

+ 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.

REQUIRED QUALIFICATIONS

+ 7+ years of experience in machine learning, statistical analysis, security, and network data to model risk-driven models of workforce behavior and provide context to security analysts to drive business decisions.

+ 7+ years of programming experience in Python and experience with machine learning libraries such as scikit-learn, TensorFlow, and PyTorch.

+ 7+ years' experience with Gen AI/LLM/NLP/MLOps or similar methodologies.

+ 3+ years of customer interfacing experience (internal or external), demonstrating excellent ability to communicate technical ideas and results to non-technical audiences.

+ 5+ year(s) of soliciting complex requirements and managing relationships with key stakeholders

+ 5+ year(s) of experience independently managing deliverables

PREFERRED QUALIFICATIONS

+ Experience developing computational methods and algorithms.

+ Experience in software development and expertise in developing and applying data science methods to anomaly detection and/or times series problems.

+ Experience in Cloud computing environment.

+ Master’s degree in data science, Mathematics, Statics

EDUCATION

Bachelor’s degree from accredited university or equivalent work experience (HS diploma + 4 years relevant experience)

BUSINESS OVERVIEW

Bring your heart to CVS Health Every one of us at CVS Health shares a single, clear purpose: Bringing our heart to every moment of your health. This purpose guides our commitment to deliver enhanced human-centric health care for a rapidly changing world. Anchored in our brand — with heart at its center — our purpose sends a personal message that how we deliver our services is just as important as what we deliver. Our Heart At Work Behaviors™ support this purpose. We want everyone who works at CVS Health to feel empowered by the role they play in transforming our culture and accelerating our ability to innovate and deliver solutions to make health care more personal, convenient and affordable. We strive to promote and sustain a culture of diversity, inclusion and belonging every day. CVS Health is an affirmative action employer, and is an equal opportunity employer, as are the physician-owned businesses for which CVS Health provides management services. We do not discriminate in recruiting, hiring, promotion, or any other personnel action based on race, ethnicity, color, national origin, sex/gender, sexual orientation, gender identity or expression, religion, age, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law. We proudly support and encourage people with military experience (active, veterans, reservists and National Guard) as well as military spouses to apply for CVS Health job opportunities.

Pay Range

The typical pay range for this role is:

$130,295.00 - $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 our comprehensive and competitive mix of pay and benefits – investing in the physical, emotional and financial wellness of our colleagues and their families to help them be the healthiest they can be. In addition to our competitive wages, our great benefits include:

+ **Affordable medical plan options,** a **401(k) plan** (including matching company contributions), and an **employee stock purchase plan** .

+ **No-cost programs for all colleagues** including wellness screenings, tobacco cessation and weight management programs, confidential counseling and financial coaching.

+ **Benefit solutions that address the different needs and preferences of our colleagues** including paid time off, flexible work schedules, family leave, dependent care resources, colleague assistance programs, tuition assistance, retiree medical access and many other benefits depending on eligibility.

For more information, visit https://jobs.cvshealth.com/us/en/benefits

We anticipate the application window for this opening will close on: 11/30/2025

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.

We are an equal opportunity and affirmative action employer. We do not discriminate in recruiting, hiring, promotion, or any other personnel action based on race, ethnicity, color, national origin, sex/gender, sexual orientation, gender identity or expression, religion, age, disability, protected veteran status, or any other characteristic protected by applicable federal, state, or local law.