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ML Infrastructure (Staff+) Engineer
About Layer Health: Layer Health is a healthcare AI company spun out of MIT and backed by GV (Google Ventures), Define Ventures, Flare Capital Partners, General Catalyst, MultiCare Health System and Froedtert Health. We are solving the information problem in healthcare by building an AI layer that can accurately and scalably synthesize information from medical records. Our mission is to reduce friction everywhere in healthcare through our LLM-powered platform that solves chart review once and for all, across use cases.
We are looking for an ML Infrastructure (Staff+) Engineer to join our engineering team in Boston or NYC (hybrid). This role requires a minimum of 6 years of work experience and involves building and maintaining robust machine learning infrastructure that powers our AI-driven healthcare solutions.
Key Responsibilities:
- Design and implement scalable ML infrastructure solutions
- Develop and maintain ML pipelines for training and deployment
- Collaborate with data scientists and ML engineers to build ML infrastructure
- Ensure ML model performance, reliability, and scalability
- Optimize ML infrastructure for cost efficiency and performance
- Monitor and maintain ML infrastructure uptime and reliability
- Participate in architecture discussions and technical planning
- Work with cloud platforms (GCP, AWS, Azure) to deploy and manage ML infrastructure
- Implement monitoring and alerting systems for ML infrastructure
- Troubleshoot and resolve ML-related issues in production
- Document technical specifications and procedures
- Mentor junior team members and share best practices
- Contribute to research and development of new ML technologies
Required Skills and Qualifications:
- Minimum of 6 years of professional software engineering experience
- Strong expertise in machine learning infrastructure and deployment
- Experience with cloud platforms (GCP preferred, AWS and Azure also acceptable)
- Proficiency in Python and/or other ML development languages
- Knowledge of ML frameworks (TensorFlow, PyTorch, Scikit-learn)
- Understanding of ML model serving and deployment techniques
- Experience with distributed computing and big data technologies
- Familiarity with containerization technologies (Docker, Kubernetes)
- Strong SQL skills and experience with relational databases
- Understanding of ML model governance, privacy, and compliance requirements
- Experience with healthcare data standards and regulations
- Knowledge of DevOps practices and CI/CD pipelines
- Excellent problem-solving abilities and analytical thinking
- Strong communication and collaboration skills
- Ability to work independently and in a team environment
- Experience with healthcare data and medical records is a plus
What You’ll Bring:
- Proven track record of building and maintaining scalable ML infrastructure
- Experience working with healthcare data and medical records
- Strong understanding of ML engineering best practices
- Experience with machine learning model deployment and serving
- Knowledge of healthcare regulatory requirements and compliance
- Ability to design and implement robust ML solutions
- Experience with modern ML stack technologies
- Passion for applying technology to solve real-world healthcare challenges
- Strong analytical and troubleshooting capabilities
- Experience with agile development methodologies
Compensation: The estimated pay range for this role is $160,000 - $220,000 annually, with competitive equity options. The position offers comprehensive benefits including unlimited PTO, medical, dental, and vision coverage, disability insurance, and retirement plans.
Work Environment: This is a hybrid role with work locations in Boston or NYC offices (2-3 days per week in-office). The engineering team values collaboration, innovation, and making a meaningful impact in healthcare through technology. We operate with a high-velocity, low-ego culture that encourages learning and growth.
Join us in building the future of healthcare through artificial intelligence and machine learning. Our mission is to transform how healthcare data is processed and utilized to improve patient outcomes and reduce healthcare friction.