Job Information
Healthfirst Sr Cloud Machine Learning Engineer in Remote, Florida
Duties & Responsibilities :
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, GitHub Actions, and AWS services (CloudWatch, X-Ray, Lambda).
Contribute to our transition to containerized, distributed architectures (Docker, OpenShift).
Mentor teammates help plan and prioritize work, and champion best practices in code quality, automation, and Agile delivery.
Additional duties as assigned.
Minimum Qualifications:
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
Preferred Qualifications:
Masters degree
Familiarity with containerization methods
Experience with health-related data
Languages: Python, SQL, Typescript
Infrastructure & Automation: Terraform, GitHub Actions, Apache Airflow
Compute: AWS Lambda, EC2, ECS, EKS
Data & Storage: AWS S3, Redshift, Glue, Athena, DynamoDB, Apache Iceberg, DBT
ML/AI: AWS SageMaker, Bedrock
Observability: AWS CloudWatch, X-Ray
WE ARE AN EQUAL OPPORTUNITY EMPLOYER. Applicants and employees are considered for positions and are evaluated without regard to mental or physical disability, race, color, religion, gender, gender identity, sexual orientation, national origin, age, genetic information, military or veteran status, marital status, mental or physical disability or any other protected Federal, State/Province or Local status unrelated to the performance of the work involved.