Manager, AI/ML Engineering
Straight from Lyra Health’s careers page. Apply on the company site — no recruiter, no middleman.
Manager, AI/ML Engineering
Team: Data Science and Machine Learning
Location: United States
Commitment: Full-time
Workplace Type: remote
Salary:
Annual salary is only one part of an employee’s total compensation package at Lyra. We also offer generous benefits that include:
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Comprehensive healthcare coverage (including medical, dental, vision, FSA/HSA, life and disability insurances)
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Lyra for Lyrians; coaching and therapy services
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Equity in the company through discretionary restricted stock units
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Competitive time off with pay policies including vacation, sick days, and company holidays
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Paid parental leave
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401K with up to 3% matching
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Monthly tech allowance
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We like to spread joy throughout the year with well-being perks and activities, surprise swag, regular community celebration…and more!
We can’t wait to meet you.
We are looking for a strategic leader to spearhead the execution of Lyras 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 teams 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.
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