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.

The Sr AIOps Engineer will partner with data engineers, data scientists, and operations teams in training, building, deploying and scaling ML models and capabilities leveraging cloud-native containerization & distributed computing technologies. (S)he will play a key role in optimizing ML pipelines for scalability and performance in an environment with very large datasets and will apply an 'Engineering Excellence' mindset by building reusable engineering products, frameworks and other automation solutions that simplify and accelerate deployment of ML solutions. The candidate will act as a trusted engineering advisor and collaborating partner working closely with customers and data scientists to enable self-service ML capabilities to optimize and simplify tasks.

• 5+ years of Data & Analytics related experience with experience in designing & developing ML pipelines and/or platforms.
• 3+ years of experience building cloud native analytical products in GCP, Azure or AWS.
• 1+ years of ML-centric programming experience with either Python(preferred), Rust, Java or R.

• Hands-on experience working in scalable distributed computation frameworks like Spark or Dask.
• Hands-on experience in developing AI solutions leveraging Python libraries such as PyTorch, Tensorflow, Scikit-Learn, Keras, and/or XGBoost.
• Familiarity with working in Dev/ML Ops model and industry deployment best practices using CI/CD tools and infrastructure as a code (e.g., Docker, Kubernetes).
• Strong interpersonal and communication skills, including the ability to explain and discuss machine learning concepts with non-technical colleagues and cross functional teams.
• Experience within an IT infrastructure domain and familiarity with telemetry/log data and concepts is highly desirable.
• Expertise with working with open-source ML platforms & toolsets such as mlflow and Feast is preferred.
• Exposure in implementing Gen AI and/or NLP based solutions using LLMs.
• Experience implementing or maintaining Feature Stores.
• Experience in deploying unsupervised machine learning, time series modeling, CNNs, ensemble models.
• Experience with online model inference.

• Bachelor's degree or equivalent experience (High School Diploma and 4 years relevant experience).