Lead Machine Learning Engineer

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.

Job Overview:

Are you a talented and motivated Machine Learning Engineer with a flair for Software Engineering? Do you thrive in a collaborative environment where your ideas can make a real impact? In this role, you will leverage your expertise to extract knowledge and insights from data to investigate complex business problems through a range of data preparation, modeling, analysis and/or visualization techniques, including predictive analysis, business intelligence, pattern recognition, operational effectiveness and/or economic forecasting. More importantly, you will create solutions that seamlessly integrate with ML models, optimize workflows, and execute ML algorithms on data sets on a larger scale. You’ll work closely with data scientists, product managers, and fellow engineers to design, implement, and optimize cutting-edge ML solutions.

Key Responsibilities:

• Innovate and Create: Design, develop, and maintain scalable software applications with complex Data/ ML solutions that push the envelope of technology.

• Performance Guru: Monitor and evaluate the performance of ML models in production, making necessary adjustments to meet high standards for performance and reliability.

• API Wizardry: Build and deploy RESTful APIs using Fast API to serve ML models and facilitate smooth data interactions, ensuring a seamless user experience.

• Collaborative Synergy: Partner with data scientists to understand model requirements and translate them into production-ready code that delivers results.

• Algorithm Alchemist: Implement and optimize algorithms for data processing, feature extraction, and model training, turning raw data into actionable insights.

• Quality Advocate: Conduct code reviews and provide constructive feedback, ensuring high-quality code and adherence to best practices that elevate our standards.

• Lifecycle Champion: Participate in the full software development lifecycle, from requirements gathering to design, implementation, testing, and deployment, ensuring a smooth process every step of the way.

• Continuous Learner: Stay ahead of the curve by keeping up to date with the latest advancements in ML and software engineering, applying new techniques and technologies to our projects.

• Knowledge Sharer: Document processes, code, and model performance to ensure knowledge sharing and maintainability, fostering a culture of learning within the team.

Required Qualifications:

• 8+ years of experience as a Software Engineer, with a focus on Machine Learning.

• Proven experience in building and scaling RAG applications using frameworks like Langchain, LLamaIndex in production.

• 7+ years of Data & Analytics, specializing in the design and development of Data & ML pipelines and/or platforms.

• 6+ years of Hands-on experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn etc.) and ML algorithms (i.e., clustering, decision trees, boosting, etc.)

• 5+ years of experience with data preprocessing, feature engineering and model evaluation

• 5+ years of experience developing production-level software with one or more languages, such as Python, Java, or C++.

• 5+ years of Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes).

• Proficiency in defining API routes using HTTP methods like GET, POST, PUT, DELETE, and adept at handling request parameters and body data.

• Strong understanding of data structures, algorithms, and software design principles.

Preferred Qualifications:

• Exposure in implementing Gen AI and/or NLP based solutions using LLMs.

• Develop Agentic AI applications and automate the orchestration workflows using Vertex AI Agent Builder, Langgraph, etc 

• Familiarity with working in Dev/ML Ops model and CI/CD tools and infrastructure as a code (e.g., Jenkins, Docker, Kubernetes).

• Knowledge of i