---
title: 'Engineering Manager, Machine Learning at Layer Health'
canonical: 'https://feeny.ai/job/engineering-manager-machine-learning-layer-health-boston-xws1mvq9myc0'
type: 'job'
last_seen: '2026-09-11'
---

# Engineering Manager, Machine Learning at Layer Health

- **Company:** Layer Health
- **Location:** Boston, MA
- **Posted:** 2025-11-17
- **Last confirmed live:** 2026-09-11
- **Apply:** https://job-boards.greenhouse.io/layerhealth/jobs/4990056008

## Job description

About us:

Layer Health was founded in 2023 by leading machine learning researchers from MIT and Harvard Medical School. We are building an AI layer that can accurately and scalably synthesize information from medical records, with the mission to reduce friction everywhere in healthcare. Our LLM-powered platform is solving chart review once and for all, across use cases. For health systems, our first product dramatically accelerates clinical registry abstraction in areas ranging from surgery and cardiology, to oncology. Our long term vision is for our AI layer to safely transform patient care and minimize unnecessary heartbreak. Layer Health’s diverse founding team brings expertise across machine learning, UI/UX, large language models, and medicine.

We’re seeking outstanding hires to join our team as early members. This is an opportunity to contribute to a high-impact, collaborative, mission-driven team, and help define the next stage of growth for Layer Health. Together, we will create the AI layer that will redefine healthcare for the better.

We’re currently looking to hire our first ML Engineering Manager to help mentor our team and oversee ML strategy. This is a hybrid role in our Boston or NYC office; you will work closely with our engineers, ML scientists, and product teams to enable our team to build ML-native enterprise platforms, ensuring scalability, efficiency, and reliability.

[Here’s a collection of articles about our product, mission, recent funding round, etc.](https://www.layerhealth.com/resources)

## What you’ll do

- Provide technical leadership and management to a small, high-leverage team of ML Engineers, Research Engineers, and ML/Data Scientists. Act as a player-coach: you’ll set direction while remaining actively involved in design, experimentation, and implementation.
- Drive the development of end-to-end ML systems—from shaping ambiguous problems into clear model requirements, training datasets, evaluation frameworks, and model architectures, to supporting reliable production deployment.
- Help craft and drive the ML technical agenda in partnership with engineering, research, and product leadership, ensuring the roadmap aligns with company goals and high-impact opportunities.
- Lead rigorous experimentation and model evaluation, ensuring our LLM systems meet clinical-grade performance and reliability requirements.
- Work closely with our engineering team to integrate and scale models in production, optimize inference efficiency, and maintain strong observability and monitoring.
- Establish and champion best practices in modeling, code quality, reproducibility, and experiment design—helping define “what incredible looks like” for ML at an early-stage, mission-driven health tech company.
- Communicate technical work clearly to cross-functional partners and leadership, translating ML developments into strategic implications for the business and product.
- Recruit, cultivate, and inspire the next generation of technical talent as the team grows.

## What we look for

- Degree in computer science, mathematics, physics, or a related field.
- 7+ years of hands-on ML experience, ideally including LLMs or NLP; healthcare exposure is a plus but not required.
- 2+ years of technical leadership experience (formal or informal) where you’ve guided teams, set direction, and mentored others and 1 or more years formal management experience.
- Deep ML expertise: model development, training workflows, data pipeline design, evaluation methodology, and production deployment.
- Strong Python fluency and experience with modern ML tooling and infrastructure.
- Comfortable owning production-level data pipelines, monitoring, and performance analysis.
- A strategic thinker who can also dive deep into hands-on implementation when needed.
- Thrives in fast-paced, high-autonomy environments with evolving requirements.
- Excellent communication and collaboration skills.
- A passion for transforming healthcare with state-of-the-art AI.

Would be nice

- Previous early stage startup experience (and a love for it)

Expected compensation range for this role is $250,000-275,000. Compensation is dependent on experience, overall fit to our role, and candidate location. Expected compensation ranges for this role may change over time. If your compensation requirement is greater than our posted salary ranges, please still consider applying to our role. We will make a determination as to whether an exception can be made.

If you are excited about this role, we encourage you to apply even if you don't feel that you meet every single requirement. We're eager to meet people that believe in our mission and can contribute to our team in a variety of ways. We welcome diverse perspectives, rigorous thinking, and fearlessness in challenging the status quo.

Layer Health is committed to fostering an environment of inclusion that is free from discrimination.  We are an Equal Opportunity Employer where employment is decided on the basis of qualifications, merit, and business need. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected Veteran status, or any other characteristic protected by law.

Join us and help us transform healthcare with AI.

## About Layer Health

## Company Overview
- **One-liner**: Layer Health provides an AI-powered clinical intelligence platform that automates medical chart review and clinical registry abstraction for health systems.
- **Entity Type**: Private (Series A-II)
- **Headquarters**: Brookline, Massachusetts, United States
- **Founded**: 2023
- **Founders**: Monica Agrawal, Divya Gopinath, David Sontag, Steven Horng

## Core Business
- **Primary industry/industries**: Healthcare AI, Clinical Informatics, Digital Health
- **Target customers**: B2B – health systems, hospitals, and life sciences organizations
- **Mission or purpose statement**: "Change how information is fundamentally processed in healthcare" by deploying AI to solve real clinical problems, ensuring the right care at the right time and place.

## Products & Services
- **Clinical Registry Automation**: AI-supported abstraction that works across service lines (cardiovascular, surgery, oncology) – validated to achieve 50%+ time savings in 10 weeks or less.
- **Custom Quality Metric Abstraction**: Automates extraction of any custom variable (e.g., SSI, discharge medicine Rx) from the full clinical record with evidence-backed accuracy.
- **Clinical Pathways**: Identifies eligible patients for high-value, guideline-aligned procedures by reasoning across the entire longitudinal record.
- **Site of Care Optimization**: Screens patients against complex protocols to decant low-acuity cases and backfill hospital capacity with more complex procedures.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Total funding raised – $33.55M (as of latest Series A-II)
- **Notable Investors/Partners**: Intermountain Health (strategic investment and multi-year AI deployment), Johns Hopkins Medicine (multi-year collaboration), White Plains Hospital
- **Growth Signals**: Named to the 2026 New York Digital Health 100; listed in CB Insights’ 50 Most Promising Digital Health Startups; multiple live implementations at leading U.S. health systems.

## Competitive Advantages
- **Elite team**: Founded by AI and clinical leaders from MIT, Harvard Medical School, and Google; team holds 200+ peer-reviewed publications
- **Validated accuracy**: Model accuracy validated on customer data and proven to match or exceed human performance
- **Continuous improvement**: Models are continuously monitored and improve with every piece of feedback
- **Native workflow integration**: AI modules integrate directly into existing clinical workflows with dedicated change management support

## Strategic Focus
- **Deepen enterprise partnerships**: Expand multi-year AI deployments with major health systems (e.g., Intermountain Health, Johns Hopkins)
- **Scale across service lines**: Move beyond initial registry automation into quality measurement, clinical guidance, and site-of-care optimization
- **Drive adoption and ROI**: Move from pilots to production with measurable time and cost savings for clients

## Why Work Here
- **Culture**: "Clinicians, scientists, and engineers" motivated by real-world impact and a shared vision of tomorrow’s healthcare world
- **Team**: Small but growing team (around 20-50 employees) with deep expertise in ML, clinical medicine, engineering, and commercial execution
- **Locations**: Hybrid/office roles based in Boston, MA (Brookline) and New York, NY; some contractor roles are fully remote
- **Engineering culture**: Heavy emphasis on machine learning, backend infrastructure, data science, and product engineering – open roles include ML Engineer, ML Scientist, Research Engineer, Fullstack Engineer, SRE, and Data Scientist
- **Perks**: Not explicitly listed, but the company offers dedicated change management and continuous improvement support to its teams

## Sources
1. [layerhealth.com (Home)](https://www.layerhealth.com/)
2. [layerhealth.com (Company)](https://www.layerhealth.com/company)
3. [greenhouse.io (Jobs)](https://job-boards.greenhouse.io/layerhealth/jobs/5025477008)
4. [cbinsights.com](https://www.cbinsights.com/company/layer-health)
5. [linkedin.com](https://www.linkedin.com/company/layerhealth)

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