AI/ML Engineering Manager

Join Lyra Health as an AI/ML Engineering Manager, where you will lead the execution of our machine learning roadmap, mentor a high-impact engineering team, and drive strategic technical influence. You will have the opportunity to cultivate an inclusive engineering culture, oversee the ML SDLC, and provide leadership through strategic architectural guidance. Enjoy benefits such as full access to mental health services, medical, dental, and vision benefits, four weeks of vacation, and more.

• Spearhead the execution of Lyra's machine learning roadmap, scaling and mentoring a high-impact AI/ML engineering team.
• Drive the quarterly planning lifecycle for AI/ML workstreams, prioritizing essential initiatives and ensuring alignment with broader business objectives.
• Collaborate with Product Management and Data Science leads to transform complex clinical requirements into robust, safety-oriented production models.

• 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