Manager, AI/ML Engineering
Summary
People-manager role leading and scaling Lyra Health's AI/ML engineering team. Day to day: owning the machine learning roadmap, mentoring engineers, running design reviews, and shipping production-grade, safety-focused ML microservices on AWS and Kubernetes for Lyra's AI-powered mental health care platform.
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.
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.
Why Lyra?
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Collaborative Innovation: Thrive on working alongside brilliant colleagues to solve complex, mission-critical challenges.
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Social Impact: Are deeply motivated by making a tangible difference and supporting individuals during their most vulnerable moments.
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Cross-Functional Partnership: Enjoy collaborating with a diverse group of physicians, therapists, data scientists, and product leaders.
Responsibilities
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Exceptional People Leadership: Facilitate technical growth through weekly 1:1s, performance management, and clearly defined career trajectories for machine learning engineers.
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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.
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Cultivate Engineering Culture: Establish an inclusive, high-performance environment by championing knowledge sharing, mentorship, and rigorous technical standards across the ML organization.
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Strategic Technical Influence: Collaborate with Product Management and Data Science leads to transform complex clinical requirements into robust, safety-oriented production models.
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ML SDLC Oversight: Maintain a high technical bar through design reviews, guiding the evolution from experimental research to stable microservices deployed on Kubernetes.
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Multiplicative Technical Vision: Provide leadership through strategic architectural guidance and prototypes, focusing on scaling your team's collective impact and technical reach.
Qualifications
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Proven experience in engineering management, specifically leading and scaling high-performing ML/AI teams within production environments.
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Exceptional People Leadership: Strong ability to develop technical talent, manage performance, and build a collaborative team culture.
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Strategic Mindset: Demonstrated experience balancing long-term technical strategy and model governance with day-to-day people leadership.
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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.
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Operational Excellence: Mastery of the ML SDLC, including dataset lineage, automated evaluation, and deploying microservices at scale.
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Cloud Architecture: Strong experience architecting cloud-native solutions on AWS (or equivalent cloud providers).
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Strategic Communication: Exceptional ability to distill highly ambiguous technical problems into clear strategic priorities and influence leadership across engineering, product, and business domain disciplines.
Preferred Qualifications
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Polyglot Engineering Background: Experience writing high-performance production code in Java or Kotlin.
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Healthcare & Sensitive Data Expertise: Experience architecting AI/ML systems within highly regulated environments (HIPAA compliance, SOC2, handling PHI/PII).
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MLOps / Platform Productization: Experience building internal developer platforms or ML tooling used by dozens of data scientists and engineers.
Skills
As published by lever · 9 questions · 4 written answers
Basics
Resume/CV, Full name, Pronouns, Email, Phone, Current location, Current company, LinkedIn URL, Twitter URL, GitHub URL, Portfolio URL, Other website, To which gender identity do you most identify?, To which sexual orientation do you most identify?, Do you identify as a person living with a disability?, Are you fluent in any of the following languages?, Do you identify as LGBTQIA+?
Pick from a list (5)
- Are you legally authorized to work in the United States for our Company?
- Do you now, or will you in the future, require sponsorship for employment visa status (e.g., H-1B visa status, etc.) to work legally for our Company in the United States?
- Are you an employee of Lyra, Bend or an affiliated company (Currently or Previously)?
- If yes to the previous question, please select your affiliation: optional
- If you are a Lyra employee, do you certify you have reviewed the Internal Mobility Policy and meet the requirements? optional
Written answers (4)
- If you selected "other", please share your relationship here optional
- What do you enjoy about people leadership?
- What specific strategies (such as quantization, distillation, or guardrailing) have you implemented to optimize model latency, reduce costs, and mitigate bias or safety concerns in production?
- Describe a production RAG system or GenAI solution (e.g., LLMs, fine-tuning, or vector retrieval) you designed and deployed. Which vector database did you use, and how did you approach indexing, retrieval quality, and latency optimization?