Posted by the employer · United States
Senior ML Engineer - ML/AI
Lyra Health · United States
Posted: 6/9/2026 · On the employer's job feed since 10/11/2026
The advert
Quoted in full from Lyra Health's job posting. Gavroche does not edit it.
About the Role
We are looking for an experienced Senior AI/ML Engineer to spearhead the design, development, and deployment of next-generation AI capabilities for our platform. In this role, you won't just train models in a sandbox—you will architect robust, scalable production systems that integrate predictive analytics, Natural Language Processing (NLP), and Generative AI to solve complex, real-world problems.
As a senior member of the team, you will bridge the gap between data science research and production-grade software engineering, while mentoring junior engineers and influencing our AI product roadmap.
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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Design, train, fine-tune, and evaluate deep learning, classical ML, and foundational GenAI models (LLMs, diffusion models) to drive core product features.
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Build, scale, and maintain robust ML pipelines for continuous training, evaluation, and real-time/batch inference using modern MLOps frameworks.
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Collaborate with backend and frontend teams to integrate AI models into microservices, ensuring low latency, high availability, and optimal resource utilization.
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Architect scalable data pipelines for preprocessing, vectorizing, and ingestion of massive structured and unstructured datasets.
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Implement rigorous evaluation frameworks for model alignment, bias mitigation, guardrailing, and cost/latency optimization (e.g., quantization, distillation).
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Provide technical leadership, conduct thorough code reviews, and mentor junior/mid-level engineers on best practices in software craftsmanship and ML engineering.
Qualifications
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6+ years of experience deploying ML/AI solutions in production environments
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Ability to write high-quality code in Python
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Experience building RAG (retrieval-augmented generation) based solutions
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Experience setting up and maintaining vector databases
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A strong desire to work on ML/AI based products
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A desire to learn new technologies quickly
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A thoughtful approach to balancing quality and deadlines in fast-paced settings
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Excellent communication skills with a talent for building consensus and alignment
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Strong organizational skills and the ability to distill complex problems into clear priorities that move the team and business forward
Preferred Qualifications
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Experience defining and using Protobuf messages
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Experience working with Docker and deploying applications to Kubernetes
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Experience with relational and low-latency databases
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Experience working with Celery
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Experience building RAG (retrieval-augmented generation) based solutions
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Experience setting up and maintaining vector databases
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Experience writing production code in Java/Kotlin
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Experience building solutions on cloud infrastructure, particularly AWS
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Experience working with highly sensitive data in a healthcare environment
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200 open data scientist roles found; at most three per employer shown. Source: Direct employer job feeds (ATS) and career sites crawled by gavroche-direct.
How data scientist roles in United States are worked
8% fully remote · 2% hybrid · 90% on-site
From 91 adverts whose ATS states a work mode. Source: Direct employer job feeds (ATS) and career sites crawled by gavroche-direct; the employers' own work-mode flags (adverts without one count as on-site).
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