Manager, AI/ML Engineering

Lyra Health is hiring a Manager, AI/ML Engineering to lead execution of its machine learning roadmap and scale an AI/ML engineering team. The role focuses on people leadership, technical strategy, and delivering reliable, production-grade machine learning systems for its mental health care platform.

Responsibilities:

• 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

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
• Strong technical foundation in machine learning systems (transformers, neural networks, fine-tuning) with the 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 domain disciplines
• 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