Senior ML Engineer (ML/AI)
At a glance
Senior Machine Learning Engineering role at Lyra Health. Remote, United States · full-time · $143,000–$197,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Design and assess deep learning, classical ML and GenAI models, including LLMs and diffusion models, for product features
- Keep model training and inference pipelines running across continuous evaluation and real-time or batch workloads
- Connect models to backend and frontend services, with attention to response time, availability and compute use
- Build data flows that prepare, vectorize and ingest structured and unstructured information
- Set standards for model evaluation, bias controls and guardrails, while reviewing code and coaching engineers
What you bring
- At least six years deploying ML or AI systems in production
- Strong Python coding skills and hands-on experience building RAG solutions
- Experience creating and maintaining vector databases
Who this fits
This senior role suits an ML engineer who can take models from development into production and guide less experienced teammates. It is a full-time remote role for candidates in the United States.
From the employer
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