Machine Learning Engineer
Layer Health10 months ago
Base Salary
$210k - $250k/yr
Responsibilities
- Translate internally developed and community LLM research into production systems that deliver customer value.
- Work with large-scale structured and unstructured clinical data in cloud-based environments.
- Develop methods and features for production model quality, including drift and performance-degradation detection.
- Build observability tooling for model performance characteristics.
- Implement robust monitoring, logging, and error handling for deployed systems.
- Collaborate with product, engineering, and research teams to improve products and develop next-generation healthcare ML systems.
- Help cultivate the company’s ML engineering and product culture.
Requirements
- 5–7+ years of experience in backend and cloud platform software development.
- Fluency in one or more backend programming languages, including Python, Golang, Rust, or Java; the team primarily uses Python.
- Familiarity with modern machine learning, LLM techniques, and frameworks.
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
- Experience developing performant, scalable, and data-centric enterprise software products.
- Experience building end-to-end ML systems spanning design, training, inference, deployment, and monitoring is a bonus, not a requirement.
- Strong problem-solving skills, attention to detail, and communication skills, including the ability to explain complex technical concepts to non-technical stakeholders.
- Adaptability, teamwork, and interest in applying AI/ML to healthcare.
Benefits
- Stock options are offered in addition to base compensation.
- Engineers are expected to meet regularly in person at the Boston or NYC office; candidates from Boston, NYC, or the East Coast are welcome.
- Mission-driven, collaborative, inclusive, and customer-focused work environment.
About Layer Health
Layer Health builds an LLM-powered platform that synthesizes information from medical records to automate chart review and accelerate clinical registry abstraction for health systems. Spun out of MIT and founded in 2023, the privately held company sells enterprise AI software to hospitals and health systems for clinical and operational workflows. It is backed by GV (Google Ventures), General Catalyst, MultiCare Health System, and Froedtert Health.