Join CVS Health as a Lead ML/AI Engineer - Transform Healthcare with Your Expertise

Bring your expertise to CVS Health. Every team member at CVS Health shares a united purpose: Bringing our heart to every moment of your health. This mission drives our commitment to deliver enhanced, human-centric health care in a rapidly evolving world. Anchored in our brand — with heart at its center — our purpose sends a personal message that how we provide our services is just as critical as what we deliver. Our Heart At Work Behaviors™ support this purpose, ensuring everyone at CVS Health feels empowered to transform our culture and accelerate innovation for personal, convenient, and affordable healthcare solutions.

Position Summary

As a Lead ML/AI Engineer at CVS Health, you will be at the forefront of designing and implementing end-to-end ML/AI and Feature lifecycle management on Azure/Google Cloud Platform. You will leverage cloud-native services and integrate them with other operational and automation tools. Your key responsibilities will include:

• Supporting the deployment of ML/AI pipelines on the platform.
• Enabling functionality for analysis, model optimization, statistical testing, model versioning, deployment, and monitoring of models and data.
• Translating functionality into scalable, tested, and configurable platform architecture and software.
• Establishing strong software engineering principles for Python development on the Azure/Google Cloud Platform.
• Delivering features aligned with enterprise AutoML, Feature Engineering, and MLOPS capabilities.
• Exhibiting innovative thinking and strong communication skills.
• Owning deliverables with design decisions aligned to scalability and industry best practices.
• Providing technical leadership and mentorship to a team of machine learning engineers. Collaborating with cross-functional teams to align ML initiatives with business goals.
• Designing, implementing, and optimizing machine learning algorithms and models. Staying abreast of the latest advancements in ML research and applying them to solve complex business problems.
• Architecting and implementing scalable and efficient machine learning systems. Collaborating with software engineers to integrate ML models into production systems.
• Working closely with data engineers to ensure the availability and quality of data for training and evaluating machine learning models.
• Developing strategies for deploying machine learning models at scale. Ensuring models are integrated into production systems with high reliability and performance.
• Designing and conducting experiments to evaluate the performance of machine learning models. Iterating on models based on feedback and evolving business requirements.

Location

This position prefers a hybrid work schedule, with in-office presence 3 days per week every other week in locations such as Dallas/Irving, Chicago, Boston/Wellesley, NYC, Hartford CT, Blue Bell PA, Scottsdale AZ, or Woonsocket RI. We will also consider 100% remote work.

Required Qualifications

• 6+ years of experience in analytics domains, with a deep understanding of ML operationalization and lifecycle management.
• 5+ years of deploying and monitoring analytical assets in batch/real-time business processes.
• 5+ years of SQL & Python programming experience with strong software development principles.
• Experience in designing and developing AI applications and systems.
• Experience with real-time and streaming technology (e.g., Azure Event Hubs, Azure Functions, Pub/Sub, Kafka, Spark Streaming).
• Experience with REST API/Microservice development using Python/Java.
• Experience with deployment/scaling of apps in containerized environments (AKS and/or GKE).
• Experience with Snowflake/BigQuery, Google Dataproc/Databricks, or big data frameworks on Spark.
• Experience with RDBMS and NoSQL Databases and hands-on query tuning/optimization.

Preferred Qualifications

• Hands-on experience building solutions using cloud-native services (Azure, GCP preferred).
• Understanding of DevOps, Infrastructure as Code, and automation for self-service.

Education

Required: Bachelor’s degree in Computer Science, Engineering, Statistics, Physics, Math, or related field or equivalent experience.

Preferred: Master’s Degree or PhD with coursework focused on advanced algorithms,