AI/ML Engineering Manager, Lyra Health

• 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
• 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

Desirable

• 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