Staff ML Engineer (ML/AI)
At a glance
Senior Machine Learning Engineering role at Lyra Health. Remote, United States · full-time · $161,000–$221,500 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Set the long-range design for ML and generative AI platforms, supporting safe, dependable model releases across the organization
- Build training, fine-tuning, and low-latency inference systems, including RAG, vector storage, and LLM evaluation safeguards
- Define AI/ML delivery practices for data lineage, CI/CD, automated testing, red-teaming, and production monitoring
- Turn clinical priorities into AI platform plans with product, data science, security, and clinical leaders
- Guide engineers through architecture reviews and mentoring, while contributing prototypes and code on critical work
What you bring
- At least eight years deploying complex ML or AI systems in critical production settings, with technical leadership experience
- Strong command of Python, REST API design, Protobuf, microservices, Docker, Kubernetes, and real-time inference
- Hands-on work designing RAG pipelines, tuning LLMs, using vector databases, and creating evaluation and guardrail systems
- Experience with relational databases, low-latency key-value stores, distributed queues, and data pipeline orchestration
- Cloud architecture experience with AWS or a comparable provider, plus the ability to turn ambiguous problems into clear priorities
Who this fits
This senior, hands-on technical leadership role suits an experienced ML engineer who can shape architecture, mentor senior engineers, and contribute code. You’ll work across engineering, product, data science, security, and clinical teams. The role is remote in the United States.
From the employer
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
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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.
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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.
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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.
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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.
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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.
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Hands-On Leadership: Lead by example through technical prototypes, critical-path architecture, and strategic coding contributions.
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And of course, you will be coding!
Qualifications
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8+ years of experience deploying complex ML/AI solutions into mission-critical production environments, with a proven track record of technical leadership.
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Deep System & Software Engineering Expertise: Mastery of Python, RESTful API design, Protobuf, and microservices architecture.
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Production AI/ML Infrastructure Mastery: Deep expertise with Docker, Kubernetes, container orchestration, and real-time inference services.
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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.
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Data Layer Systems: Expertise with relational databases, low-latency key-value stores, distributed queueing system architectures (e.g., Celery, Kafka), and data pipeline orchestration.
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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.