Sr Cloud Machine Learning Engineer

The Senior Machine Learning Engineer will help to design data science systems. Coordinate with enterprise analytics leadership, IT partners and business stakeholders to understand their needs, inform system design and help implement complex solutions. About Healthfirst, Enterprise Analytics For over 30 years, Healthfirst has been serving New Yorkers. We helped pioneer the value-based healthcare model—where hospitals and physicians are paid based on patient outcomes—because our company was founded on the belief that insurers need to be true partners in the health system.

Enterprise Analytics is a fast paced, innovative team. Our mission is to drive personalized, relevant interactions that help our members live healthier lives. Insights from this team focus on improving health outcomes, increasing member satisfaction, making our business units more efficient and continuing to grow as a company. We’re looking for curious problem solvers to continue to push us forward.

If you are member-focused, collaborative and passionate about data come join our growing community of 70+ analysts, engineers and data scientists. Join our team to help build and scale Healthfirst’s MLOps and GenAI enablement. The team designs, builds, and maintains machine learning and data pipelines, feature stores, and internal GenAI applications — as well as the tooling and automation that streamline the industrialization of data science work across the enterprise.

This is a hands‑on senior engineering role in a collaborative team that values excellence, pragmatism, and mentorship.

• Design, build, and maintain scalable ML and data pipelines, including feature stores and MLOps infrastructure.
• Develop and deploy GenAI applications using AWS Bedrock and related frameworks.
• Collaborate closely with data scientists, engineers, and business partners to create reproducible, observable ML systems.
• Automate and improve our deployment and observability stack using Terraform, Git Hub Actions, and AWS services (Cloud Watch, X‑Ray, Lambda).
• Contribute to our transition to containerized, distributed architectures (Docker, Open Shift).
• Mentor teammates help plan and prioritize work, and champion best practices in code quality, automation, and Agile delivery.
• Additional duties as assigned.

• BS in Computer Science or related discipline
• Five (5) years of experience using scripting or programming languages
• Three (3) years of experience managing the end-to-end ML model life cycle
• One (1) year of experience deploying ML solutions with cloud computing services (e.g., AWS)
• Experience working with semi-structured and unstructured data
• Excited about being a part of the decision‑making process

• Masters degree
• Familiarity with containerization methods
• Experience with health‑related data
• Languages:
  
  Python, SQL, Typescript
• Infrastructure & Automation:
  Terraform, Git Hub Actions, Apache Airflow
• Compute: AWS Lambda, EC2, ECS, EKS
• Data & Storage: AWS S3, Redshift, Glue, Athena, Dynamo
  
  DB, Apache Iceberg, DBT
• ML/AI: AWS Sage Maker, Bedrock
• Observability: AWS Cloud Watch, X‑Ray

• Greater New York City Area (NY, NJ, CT residents): $134,600 - $194,480
• All Other Locations (within approved locations): $119,600 - $177,905

As a candidate for this position, your salary and related elements of compensation will be contingent upon your work experience, education, licenses and certifications, and any other factors Healthfirst deems pertinent to the hiring decision.

In addition to your salary, Healthfirst offers employees a full range of benefits such as, medical, dental and vision coverage, incentive and recognition programs, life insurance, and 401k contributions (all benefits are subject to eligibility requirements). Healthfirst believes in providing a competitive compensation and benefits package wherever its employees work and live.

The hiring range is defined as the lowest and highest salaries that Healthfirst in “good faith” would pay to a new hire, or for a job promotion, or transfer into this role.