Staff ML Engineer (ML/AI)

About Lyra Health
Lyra Health is a leading provider of evidence-based mental health care, serving more than 20 million people globally in partnership with employers and more than 100 million through health plan and partner relationships. The company has delivered more than 15 million sessions of mental health care, published more than 35 peer-reviewed studies, and delivered unmatched outcomes in terms of access, clinical effectiveness, and cost efficiency. Extensive peer-reviewed research confirms Lyra’s transformative care model helps people recover twice as fast and results in a 26% annual reduction in overall healthcare claims costs. Lyra is transforming access to life-changing mental health care through Lyra Empower, the only fully integrated, AI-powered platform combining the highest-quality care and technology solutions.

Responsibilities
Drive AI Platform Architecture: Design and execute the long-term roadmap for Lyra’s machine learning and generative AI platform, enabling fast, safe, and reliable deployment of frontier models across the company. Lead AI Infrastructure Vision: Architect end-to-end training, fine-tuning, and low-latency inference platforms, including centralized RAG architecture, vector databases, and enterprise evaluation/guardrail frameworks. Set Engineering Excellence Standards: Establish organizational standards for the full AI/ML SDLC—from dataset lineage and CI/CD pipelines to automated model evaluation, red-teaming, and production monitoring. Cross-Functional Technical Leadership: Partner closely with Product Management, Data Science, Security, and Clinical leaders to translate strategic clinical goals into foundational AI capability roadmaps. Mentor and Multiply Impact: Elevate the engineering culture by mentoring Senior ML Engineers, conducting high-leverage architectural reviews, and establishing engineering best practices across teams. Hands-On Leadership: Lead by example through technical prototypes, critical-path architecture, and strategic coding contributions. And of course, you will be coding!

Qualifications
8+ years of experience deploying complex ML/AI solutions into mission-critical production environments, with a proven track record of technical leadership. Deep System & Software Engineering Expertise: Mastery of Python, RESTful API design, Protobuf, and microservices architecture. Production AI/ML Infrastructure Mastery: Deep expertise with Docker, Kubernetes, container orchestration, and real-time inference services. Modern Generative AI Architecture: Hands-on experience designing and deploying RAG pipelines, fine-tuning LLMs, managing vector databases, and building robust LLM evaluation/guardrail frameworks. Data Layer Systems: Expertise with relational databases, low-latency key-value stores, distributed queueing system architectures (e.g., Celery, Kafka), and data pipeline orchestration. 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.

Preferred Qualifications
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.

"We are an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information or any other category protected by law.
 
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