Machine Learning Engineer -- Patient Safety Analytics Engineering

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.

We are seeking a highly skilled and passionate Machine Learning Engineer with a strong foundation in data engineering to join our innovative team. In this role, you will bridge the gap between data and impactful machine learning models. You will be responsible for the entire ML lifecycle, from data collection and preprocessing to model development, deployment, and monitoring, leveraging your expertise in data engineering to build robust and scalable solutions.

Responsibilities:

• Design, develop, and deploy scalable and high-performance data pipelines using GCP services (e.g., Dataflow, Dataproc, Pub/Sub, BigQuery, Cloud Storage)
• Develop and implement machine learning models using appropriate algorithms and techniques. This includes model selection, training, tuning, and evaluation.
• Use software development best practices like code review, continuous integration, and continuous delivery (CI/CD), release management, and version control.
• Develop and maintain data quality checks and monitoring systems to ensure data accuracy and completeness.
• Collaborate with data scientists and machine learning engineers to optimize data for model training and inference.
• Build and maintain data infrastructure for AI/ML workloads, including feature stores, model registries, and experiment tracking systems.
• Automate data pipelines and infrastructure using tools like Apache Airflow or similar orchestration platforms.
• Troubleshoot and resolve data-related issues and performance bottlenecks.
• Stay up to date with the latest advancements in data engineering, cloud computing, and AI/ML technologies.
• Work to enhance existing test automation processes, improving efficiency, and reducing manual intervention across environments.
• Partner with teams and serve as cross-functional expert to provide bench-marked solutions to multiple, complex technical projects/initiatives using multiple interlocking technologies.
• Implement data quality checks and monitoring to ensure data accuracy and reliability for model training and prediction.

Required Qualifications:

• 2+ years of experience as a Machine Learning Engineer, with a demonstrable understanding of data engineering principles.
• Strong programming skills in Python and experience with relevant ML libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Solid understanding of various machine learning algorithms and techniques (e.g., regression, classification, clustering, deep learning).
• Experience with data engineering tools and technologies (e.g., Spark, SQL databases, NoSQL databases, cloud platforms like AWS, GCP, or Azure).
• Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker).
• Experience with containerization technologies (e.g., Docker, Kubernetes).
• Excellent problem-solving, communication, and collaboration skills.

Preferred Qualifications:

• Experience with Azure Kubernetes Service (AKS) or Google Kubernetes Engine (GKS) for deploying containerized applications.
• Proficiency with cloud data platforms such as Snowflake and/or BigQuery.
• Experience with big data frameworks like Apache Spark, Google Dataproc, or Databricks.
• Experience with Kafka for real-time data streaming.
• Experience with REST API/Microservice development using Python.
• Experience with orchestrating data workflow using automation tools such as Airflow.
• Retail and/or Healthcare experience and domain knowledge.
• Exposure to DevOps tools such as Jenkins, GitHub, or GitLab for CI/CD pipeline management.
• Experience working in multi-developer environment, using version control

Education

• Required: bachelor’s degree in computer science, Engineering, Machine Learning, or related field or equivalent experience.
• Preferred: master’s degree with coursework focused on advanced algorithms, mathematics in computing, data structures, etc.

Anticipated Weekly Hours

Time Type

Pay Range

The typical pay range for this role is:

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. 
 

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

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