Full-Time

ML Research Engineer

Layer Health

Layer Health

51-200 employees

AI platform for clinical chart review

Compensation Overview

$160k - $200k/yr

+ Stock Options

Boston, MA, USA + 1 more

More locations: New York, NY, USA

In Person

Category
AI & Machine Learning (1)
Required Skills
Rust
Python
TensorFlow
PyTorch
Java
Go
DevOps

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Requirements
  • 3+ years of experience in building ML-native backend infrastructure.
  • 5-7+ years of experience in backend and cloud platform software development, with the ability and flexibility to traverse the stack when necessary.
  • Fluency in one or more backend programming languages including Python, Golang, Rust, Java (we use Python).
  • Familiarity with modern ML/LLM techniques and frameworks.
  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field.
  • Experience in 0-to-1 development of end-to-end ML systems (design, training, inference, deployment, and monitoring; bonus if involving LLMs).
  • Experience developing and maintaining performant, scalable, and data-centric enterprise software products.
  • Strong problem-solving skills and attention to detail.
  • Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
  • An excited and adaptable team player who wants to disrupt the healthcare industry with AI/ML, alongside an awesome team, in a customer-focused and fast-paced environment.
  • We are a Boston-based company, and expect engineers to meet regularly in-person in either our NYC or Boston office (engineers from Boston, NYC, or east coast are welcome).
Responsibilities
  • Architect efficient, secure, reliable, and performant ML pipelines and infrastructure.
  • Design, develop, and maintain scalable/data-centric backend infrastructure for our product.
  • Translate start-of-the-art LLM research (both internally developed and from the community) into production, delivering value for our customers.
  • Work with complex, large-scale, real-world clinical data (both structured and unstructured data) in a cloud-based environment.
  • Develop methods and features to ensure high-quality results for our production models (methods to detect drift/performance degradation; develop observability tooling for performance characteristics, etc.).
  • Collaborate with the broader product, engineering, and research teams to improve our products and build the next-generation of ML for healthcare.
  • Build scalable infrastructure to ensure we can scalably support efficient model development and deployment pipelines, CI/CD, testing/experimentation.
  • Ensure robust monitoring, logging, and error handling for deployed systems.
  • Stay updated on the latest advancements in machine learning and AI.
  • Cultivate a robust ML engineering and product culture that drives the company forward.

Layer Health builds an enterprise AI platform for healthcare chart review. It uses a healthcare-focused large language model (LLM) to analyze longitudinal patient charts, enabling clinicians and life sciences teams to answer complex clinical questions, automate clinical registries, and generate quality measurements. The system works by processing patient charts through modules that support registry data submission, real-world evidence abstraction, and patient registries, with emphasis on accuracy, configurability, and security. It differentiates itself from competitors through healthcare-specific validation, enterprise-grade security/compliance, and a broad set of use cases tailored to both health systems and life sciences, enabling faster, more reliable data analysis with fewer administrative burdens. Its goal is to streamline chart review, improve data quality, and free clinicians to focus more on patient care by delivering actionable insights and reliable data faster.

Company Size

51-200

Company Stage

Series A

Total Funding

$25M

Headquarters

Brookline, Massachusetts

Founded

2023

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Simplify Jobs

Simplify's Take

What believers are saying

  • Layer Health raised $21 million Series A in March 2025, extending runway.
  • Froedtert reported 65% faster abstraction, strengthening sales claims and references.
  • ACS and Johns Hopkins partnerships expand into research and oncology registries through 2026.

What critics are saying

  • Epic, Optum, and point-solutions can bundle chart abstraction into broader contracts by 2027.
  • Validation dependence on hospital-specific workflows slows rollouts and exposes accuracy failures.
  • If registry buyers distrust LLM evidence trails, Layer Health becomes a pilot-only vendor.

What makes Layer Health unique

  • MIT-spun Layer Health automates clinical registry abstraction with longitudinal-chart LLMs.
  • Intermountain Health deployment spans 33 hospitals, proving enterprise workflow depth.
  • Johns Hopkins Medicine chose Layer Health for multi-year registry automation in 2025.

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Benefits

401(k) Retirement Plan

Stock Options

Wellness Program

Remote Work Options

Hybrid Work Options

Flexible Work Hours

Growth & Insights and Company News

Headcount

6 month growth

-1%

1 year growth

1%

2 year growth

-3%
EIN Presswire
Jun 17th, 2025
Layer Health Receives Strategic Investment and Multi-Year AI Deployment with Intermountain Health

Collaboration brings AI-powered medical chart review for clinical registry reporting to drive care quality, operational efficiency across multi-state footprint

RamaOnHealthcare
Jun 17th, 2025
AI takes on clinical data at Intermountain Health

Salt Lake City-based Intermountain Health is partnering with health AI company Layer Health to streamline how it manages clinical data.

Yesil Science
May 22nd, 2025
White Plains Hospital Collaborates with Layer Health for Enhanced Clinical Registry Reporting

In March, Layer Health successfully raised $21 million in Series A funding, led by Define Ventures, with participation from notable investors such as Google Ventures, Flare Capital Partners, and MultiCare Capital Partners.

Healthcare IT Today
Apr 29th, 2025
Layer Health Secures $21M to Revolutionize AI Chart Review

Layer Health has raised $21 million in Series A funding to enhance its AI platform for medical chart review. Led by Define Ventures, with participation from Flare Capital Partners, GV, and MultiCare Capital Partners, the funding will help scale the platform, grow the team, and improve healthcare efficiency. The AI leverages large language models to extract insights from medical records, reducing costs and improving patient care. The platform is already delivering significant returns for early partners.

OOJO
Apr 2nd, 2025
Big Tech is Investing Heavily Into the Future of AI Healthcare and So Can You

Meanwhile, private firm Layer Health secured $21 million in new funding to tackle the challenge of scaling AI in healthcare, with backing from Define Ventures, Flare Capital Partners, GV, and MultiCare Capital Partners.