Metric Bio
Overview
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. Seniority level: Mid-Senior level Employment type: Full-time
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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. Seniority level: Mid-Senior level Employment type: Full-time
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