Note: The job is a remote job and is open to candidates in USA. Lyra Health provides evidence-based mental health care through an AI-powered platform and technology solutions. The Manager, AI/ML Engineering will lead the execution of the machine learning roadmap, scale and mentor an AI/ML engineering team, and ensure production-grade systems meet clinical precision and high-availability standards. The role also oversees technical strategy, cross-functional collaboration, ML software development lifecycle practices, and engineering culture.
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
Skills
- Proven experience in engineering management, specifically leading and scaling high-performing ML/AI teams within production environments
- Exceptional People Leadership: Strong ability to develop technical talent, manage performance, and build a collaborative team culture
- 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
- Operational Excellence: Mastery of the ML SDLC, including dataset lineage, automated evaluation, and deploying microservices at scale
- Cloud Architecture: Strong experience architecting cloud-native solutions on AWS (or equivalent cloud providers)
- Strategic Communication: Exceptional ability to distill highly ambiguous technical problems into clear strategic priorities and influence leadership across engineering, product, and business domain disciplines
- Polyglot Engineering Background: Experience writing high-performance production code in Java or Kotlin
- Healthcare & Sensitive Data Expertise: Experience architecting AI/ML systems within highly regulated environments (HIPAA compliance, SOC2, handling PHI/PII)
- MLOps / Platform Productization: Experience building internal developer platforms or ML tooling used by dozens of data scientists and engineers
Benefits
- Full-time employment
- Remote work arrangement
- Weekly 1:1s, performance management, and clearly defined career trajectories for machine learning engineers
- Knowledge sharing and mentorship
Company Overview
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