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Lyra Health is a leading provider of evidence-based mental health care serving over 20 million people globally. The company has delivered 15+ million mental health sessions and published 35+ peer-reviewed studies demonstrating clinical effectiveness and cost efficiency. Lyra is transforming mental health access through Lyra Empower, a fully integrated AI-powered platform combining high-quality care with technology solutions.
In this Manager role, you will lead and scale a high-performing ML/AI engineering team within a production healthcare environment. You will own the quarterly planning lifecycle for AI/ML workstreams, prioritizing initiatives like clinical program mapping while ensuring alignment with business objectives. You will facilitate technical growth through weekly 1:1s, performance management, and clearly defined career trajectories for machine learning engineers.
Key responsibilities include establishing an inclusive, high-performance engineering culture by championing knowledge sharing, mentorship, and rigorous technical standards. You will collaborate with Product Management and Data Science leads to transform complex clinical requirements into robust, safety-oriented production models. You will maintain a high technical bar through design reviews, guiding the evolution from experimental research to stable microservices deployed on Kubernetes. You will provide strategic architectural guidance and prototypes, focusing on scaling your team's collective impact and technical reach.
You will also oversee ML SDLC practices including dataset lineage, automated evaluation, and deploying microservices at scale. Strategic communication is essential—you will distill highly ambiguous technical problems into clear strategic priorities and influence leadership across engineering, product, and business disciplines.
REQUIREMENTS:
- Proven experience in engineering management, specifically leading and scaling high-performing ML/AI teams within production environments
- Strong ability to develop technical talent, manage performance, and build a collaborative team culture
- Demonstrated experience balancing long-term technical strategy and model governance with day-to-day people leadership
- Deep ML/AI domain expertise with strong technical foundation in machine learning systems (transformers, neural networks, fine-tuning) and ability to lead others in these domains
- Mastery of the ML SDLC, including dataset lineage, automated evaluation, and deploying microservices at scale
- Strong experience architecting cloud-native solutions on AWS or equivalent cloud providers
- Exceptional ability to distill highly ambiguous technical problems into clear strategic priorities and influence leadership across engineering, product, and business disciplines
PREFERRED QUALIFICATIONS:
- Experience writing high-performance production code in Java or Kotlin
- Experience architecting AI/ML systems within highly regulated environments (HIPAA compliance, SOC2, handling PHI/PII)
- Experience building internal developer platforms or ML tooling used by dozens of data scientists and engineers
