资深机器学习工程师（ML/AI）

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

"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."

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