AI/ML Engineering Manager

Lyra Health; United States; On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Mental health benefits

Medical, dental, and vision coverage

One Medical membership

Paid vacation & holidays

Monthly tech stipend

401k and equity options

Job summary

Lyra Health seeks an experienced engineering leader to spearhead the execution of our machine learning roadmap. You will scale and mentor a high-impact AI/ML engineering team, ensuring production-grade systems with clinical precision and high-availability reliability.

You will balance long-term strategy with hands-on leadership, shaping cross-functional partnerships and fostering engineering excellence within an AI-driven healthcare platform.

Qualifications

• Strategic mindset balanced with team leadership and governance.
• Deep ML/AI knowledge to guide production-grade models.
• Cloud-native architecture experience with AWS or similar.
• Proven ability to mentor and scale ML/AI teams.
• Mastery of ML SDLC including lineage and evaluation.

Responsibilities

• Lead and scale a high-impact ML/AI engineering team.
• Own and drive the quarterly AI/ML roadmap and initiatives.
• Collaborate with Product Management and Data Science to translate clinical needs into production models.
• Establish a culture of operational excellence and rigorous technical standards across ML org.

Skills

Strategic mindset

ML/AI domain expertise

Cloud architecture

People leadership

ML SDLC expertise

Strategic communication

Engineering management experience

MLOps / platform tooling

Healthcare data compliance

Java/Kotlin production code

Tools

Kubernetes

AWS

Job description

• We are looking for a strategic leader to spearhead the execution of Lyra’s machine learning roadmap. In this capacity, you will scale and mentor a high-impact AI/ML engineering team, ensuring our technical vision translates into production-grade systems that operate with clinical precision and high-availability reliability
• Exceptional People Leadership: Facilitate technical growth through weekly 1:1s, performance management, and clearly defined career trajectories for machine learning engineers
• Roadmap & Strategy Ownership: Drive the quarterly planning lifecycle for AI/ML workstreams, prioritizing essential initiatives like clinical program mapping while ensuring alignment with broader business objectives
• Cultivate Engineering Culture: Establish an inclusive, high-performance environment by championing knowledge sharing, mentorship, and rigorous technical standards across the ML organization
• Strategic Technical Influence: Collaborate with Product Management and Data Science leads to transform complex clinical requirements into robust, safety-oriented production models
• ML SDLC Oversight: Maintain a high technical bar through design reviews, guiding the evolution from experimental research to stable microservices deployed on Kubernetes
• Multiplicative Technical Vision: Provide leadership through strategic architectural guidance and prototypes, focusing on scaling your team’s collective impact and technical reach

Benefits

• Full access to Lyra’s mental health services for employees and their eligible dependents at no charge
• Medical, dental, and vision benefits, and free monthly membership to One Medical
• Four weeks of vacation and paid holidays
• Monthly tech stipend
• 401k and equity options

The ideal candidate is an experienced engineering manager who excels at balancing long-term technical strategy with hands‑on people leadership. You possess a deep passion for developing technical talent, building robust cross‑functional partnerships, and cultivating a culture of operational excellence within an AI‑driven organization

• Strategic Mindset: Demonstrated experience balancing long-term technical strategy and model governance with day‑to‑day people leadership
• Deep ML/AI Domain Expertise: Strong technical foundation in machine learning systems (transformers, neural networks, fine‑tuning) with the ability to lead others in these domains
• Cloud Architecture: Strong experience architecting cloud‑native solutions on AWS (or equivalent cloud providers)
• Exceptional People Leadership: Strong ability to develop technical talent, manage performance, and build a collaborative team culture
• Operational Excellence: Mastery of the ML SDLC, including dataset lineage, automated evaluation, and deploying microservices at scale
• Strategic Communication: Exceptional ability to distill highly ambiguous technical problems into clear strategic priorities and influence leadership across engineering, product, and business domain disciplines
• Proven experience in engineering management, specifically leading and scaling high‑performing ML/AI teams within production environments
• MLOps / Platform Productization: Experience building internal developer platforms or ML tooling used by dozens of data scientists and engineers
• Healthcare & Sensitive Data Expertise: Experience architecting AI/ML systems within highly regulated environments (HIPAA compliance, SOC2, handling PHI/PII)
• Polyglot Engineering Background: Experience writing high‑performance production code in Java or Kotlin