Sr Machine Learning Engineer - ML Ops

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.

It’s a new day in healthcare!
Combining CVS Health and Aetna was a ground-breaking moment for our company and our industry, establishing CVS Health as the nation’s premier health innovation company. Through our health services, insurance plans and community pharmacists, we’re pioneering a bold new approach to total health.
 

Join the Enterprise Consumer Analytics team for an opportunity to leverage advanced analytics, experimentation, causal inference, and strategic problem solving to helps grow CVS’ customer journeys through franchise by identifying opportunities and optimizing customer strategies derived by analyzing trends in customer shopping behavior, needs, intents, and responses. The team leverages advanced analytics, machine learning and a hypothesis-driven approach to quickly transform data into actionable, customer-centric insights in fast-moving and energizing environment. We are looking for the best, the brightest and the most passionate analytics visionaries to join our team and help us deliver on this initiative.

The Senior Machine Learning Engineer is an exciting opportunity to work data

The Senior Machine Learning Engineer is an exciting opportunity to work data related to a wide range of customer interactions and analytics. This role will be responsible for end-to-end, large scale deep learning model design, development and deployment with support from data engineering and DevOps. This role requires continuous learning and improvement for both the business subject matter expertise and emerging algorithms, techniques and their applications. Moreover, in this role you will establish software and ML development best practices, create workflow efficiencies, mentor junior team members, work with distributed computing for model training, and serve as the go-to MLOPS expert for the rest of the team.

Additional responsibilities include:

Build and facilitate deep learning model development and serving across large scale systems, enabling continuous model deployment, retraining and updates in partnership with data engineering.

Develop and participate in presentations including technical design and product strategy reviews with existing and prospective constituents on analytics results and solutions.

Interact with internal and external peers and managers to exchange complex information related to areas of specialization.

To be successful in this role, you must come from a background in software engineering with a strong knowledge of designing and building scalable and data intensive machine learning products on GCP or other cloud platforms.

Required Qualifications

• 3-5 or more years of progressively complex related experience

• 3+ years of experience developing and productionizing reinforcement learning models at scale

• 3+ years of continuous integration/development (CI/CD), integration testing, test-driven development, code versioning (Git)

• 3+ years of software development, Python, and MLOPS best practices

• 3+ years of experience in GCP or similar cloud platform

Preferred Qualifications

• Experience productionizing transformers and large language models is a strong plus

• Experience in software engineering experience / ML engineering

• AI/ML/Reinforcement learning-research (academic or industry) experience

• Demonstrates strong ability to design and build distributed data-intensive products

• Experience conducting or participating in code review a plus

• Anticipates and prevents problems and roadblocks before they occur

• Experience in Causal Inference is a plus

• Demonstrates proficiency in most areas of mathematical analysis methods, machine learning, statistical analyses, and predictive modeling and in-depth specialization in some areas

Education

• Bachelor's degree or equivalent work experience in Computer Science, Mathematics, Statistics, Economics, Physics, Engineering, or related discipline.

• Master’s degre