Senior ML Engineer (ML/AI)

Lyra Health is hiring a Senior ML Engineer (ML/AI) for a remote role open to applicants in United States. It pays $143k-$197k a year and Level rates it ; you can apply on Lyra Health.

Level's read on this job

Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
The posting lists this role as remote.
Tools and skills the posting cites include RAG, MLOps and NLP.
Level classifies it as a senior role.
Level lists 481 other open roles at Lyra Health.

AI in this role

ragml-opsnlp

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.

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:

Thrive on working with brilliant teammates to solve complex, meaningful problems
Are passionate about making a social impact and supporting people at their most challenging moments
Enjoy cross-functional collaboration with physicians, therapists, data scientists, data analysts and product managers

Responsibilities

Design, train, fine-tune, and evaluate deep learning, classical ML, and foundational GenAI models (LLMs, diffusion models) to drive core product features.
Build, scale, and maintain robust ML pipelines for continuous training, evaluation, and real-time/batch inference using modern MLOps frameworks.
Collaborate with backend and frontend teams to integrate AI models into microservices, ensuring low latency, high availability, and optimal resource utilization.
Architect scalable data pipelines for preprocessing, vectorizing, and ingestion of massive structured and unstructured datasets.
Implement rigorous evaluation frameworks for model alignment, bias mitigation, guardrailing, and cost/latency optimization (e.g., quantization, distillation).
Provide technical leadership, conduct thorough code reviews, and mentor junior/mid-level engineers on best practices in software craftsmanship and ML engineering.

Qualifications

6+ years of experience deploying ML/AI solutions in production environments
Ability to write high-quality code in Python
Experience building RAG (retrieval-augmented generation) based solutions
Experience setting up and maintaining vector databases
A strong desire to work on ML/AI based products
A desire to learn new technologies quickly
A thoughtful approach to balancing quality and deadlines in fast-paced settings
Excellent communication skills with a talent for building consensus and alignment
Strong organizational skills and the ability to distill complex problems into clear priorities that move the team and business forward

Preferred Qualifications

Experience defining and using Protobuf messages
Experience working with Docker and deploying applications to Kubernetes
Experience with relational and low-latency databases
Experience working with Celery
Experience building RAG (retrieval-augmented generation) based solutions
Experience setting up and maintaining vector databases
Experience writing production code in Java/Kotlin
Experience building solutions on cloud infrastructure, particularly AWS
Experience working with highly sensitive data in a healthcare environment

"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. By applying for this position, you acknowledge that your personal information will be processed as per the Lyra Health Workforce Privacy Notice. Through this application, to the extent permitted by law, we will collect personal information from you including, but not limited to, your name, email address, gender identity, employment information, and phone number for the purposes of recruiting and assessing suitability, aptitude, skills, qualifications, and interests for employment with Lyra. We may also collect information about your race, ethnicity, and sexual orientation, which is considered sensitive personal information under the California Privacy Rights Act (CPRA) and special category data under the UK and EU GDPR. Providing this information is optional and completely voluntary, and if you provide it you consent to Lyra processing it for the purposes as described at the point of collection, for example for diversity and inclusion initiatives. If you are a California resident and would like to limit how we use this information, please use the Limit the Use of My Sensitive Personal Information form. This information will only be retained for as long as needed to fulfill the purposes for which it was collected, as described above. Please note that Lyra does not “sell” or “share” personal information as defined by the CPRA. Outside of the United States, for example in the EU, Switzerland and the UK, you may have the right to request access to, or a copy of, your personal information, including in a portable format; request that we delete your information from our systems; object to or restrict processing of your information; or correct inaccurate or outdated personal information in our systems. These rights may be subject to legal limitations. To exercise your data privacy rights outside of the United States, please contact globaldpo@lyrahealth.com. For more information about how we use and retain your information, please see our Workforce Privacy Notice."

How we rate this

Senior ML Engineer (ML/AI) at Lyra Health rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior ML Engineer (ML/AI) is an open job at Lyra Health.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $143k-$197k a year.
The role is based in United States and is marked remote.
The job was posted on June 9, 2026.
Seniority: senior.
Applications are handled by Lyra Health. Apply on Lyra Health

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGML OpsNLP

Also common in machine learning engineer jobs at this level

Machine learning PyTorch TensorFlow C++Spark Fine-tuning

Pay

This job starts at: $143k
Typical machine learning engineer job: $198k

This posting starts 28% below the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you monitor a model once it's live, and how do you know it needs retraining?
What NLP problem have you worked on, and how did you measure whether it actually worked?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: RAG, ML Ops, and NLP. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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