ML Infrastructure Engineer (Staff+)

About Layer Health: Founded by experts from MIT and Harvard Medical School, Layer Health is building an AI layer for medical chart review. We’ve raised $21M Series A and are scaling our platform to serve healthcare systems and research organizations.

About The Role: As an ML Infrastructure Engineer, you’ll design and implement the scalable systems that power our AI-powered chart review platform. This role requires a minimum of 6 years of experience in machine learning infrastructure and will involve working closely with our data science and engineering teams.

Key Responsibilities:

• Design and maintain scalable ML infrastructure for our platform
• Optimize data processing pipelines for medical record analysis
• Collaborate with data scientists to implement and deploy ML models
• Ensure high availability and performance of our ML systems
• Develop tools and frameworks to support our growing ML ecosystem
• Partner with engineering teams to integrate ML capabilities into our products
• Contribute to our cloud infrastructure on GCP

Required Skills:

• Minimum 6 years of experience in ML infrastructure
• Deep understanding of distributed systems and cloud computing
• Experience with containerization (Docker, Kubernetes)
• Knowledge of machine learning frameworks and MLops practices
• Strong Python programming skills
• Experience with cloud platforms, particularly GCP services
• Familiarity with healthcare data and medical record systems

Ideal Candidate:

• Passionate about applying ML to solve healthcare challenges
• Experience building large-scale ML systems in production
• Strong background in distributed systems and cloud architecture
• Ability to work effectively with data scientists and engineers
• Experience with model deployment, monitoring, and maintenance
• Familiarity with healthcare data privacy and compliance requirements
• Commitment to operational excellence and system reliability

Compensation: Competitive base salary + equity package