Job Details

Metric Bio is recruiting on behalf of a San Francisco–based digital health company that is building an AI-powered platform to transform patient care and healthcare delivery. We are seeking a Machine Learning Engineer who is passionate about applying advanced ML techniques to solve complex challenges in healthcare. This is an opportunity to work on a modern stack with a team that values hands-on technical depth, collaboration, and mission-driven impact.

Responsibilities:

• Design, train, and optimize machine learning models for healthcare applications, including natural language processing, patient risk scoring, and workflow automation.
• Develop and maintain production-grade ML pipelines using MLOps tools (MLflow, Kubeflow, SageMaker, or similar).
• Collaborate with software engineers, data scientists, and clinicians to integrate ML models into scalable production systems.
• Contribute hands-on to engineering across the company's technical stack: Python/Django, Vue, Kubernetes, and GCP.
• Ensure reliability, fairness, and compliance of models with healthcare standards (HIPAA, HITRUST).
• Participate in code reviews, pair programming, and architecture discussions as part of a collaborative engineering culture.

Qualifications:

• 3–6 years of experience as a Machine Learning Engineer, Applied ML Scientist, or related role.
• Strong programming skills in Python and deep familiarity with frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Hands-on experience deploying ML models into production environments.
• Cloud expertise, ideally with GCP; Kubernetes and containerization experience preferred.
• Knowledge of healthcare data formats (FHIR, HL7) or experience with digital health systems strongly preferred.
• Excellent communication and problem-solving skills, with the ability to collaborate across technical and clinical teams.
• Passion for leveraging AI to improve patient outcomes and healthcare delivery.