À propos de ce poste Staff ML Engineer (ML/AI) chez Lyrahealth
About the Role
We are seeking a Staff ML/AI Engineer to define and drive the architectural vision for Lyra’s machine learning and generative AI technology landscape. In this role, you will serve as a technical anchor across the engineering and data organizations—architecting enterprise-scale AI platforms, setting technical strategy for high-impact AI/ML initiatives, and ensuring our AI products operate with top-tier reliability, security, and medical precision.
The ideal candidate is a seasoned technical leader who excels at translating complex healthcare challenges into scalable platform solutions, building consensus across cross-functional leadership, and elevating the technical bar for the entire engineering organization.
Lyra is for you if you
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Thrive on working with brilliant teammates to solve complex, meaningful problems
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Are passionate about making a social impact and supporting people at their most challenging moments
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Enjoy cross-functional collaboration with physicians, therapists, data scientists, data analysts and product managers
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.
