Jobs / United States / Lyra Health

Lyra Health

Clinical Product Specialist, AI Development

Remote (USA) · Remote · US only Posted today

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Skills this job asks for

Mental healthCommunicationMachine learningdbt

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Where you can work from

United States only

Based on the listing's location: Remote (USA).

The company's headquarters is not the same as where you may work from. Visa sponsorship only matters if you would relocate; see below.

Visa sponsorship, if you would relocate

Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 2 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest May 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 2 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest May 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

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 a clinical scientist who is passionate about leveraging state of the art technology, particularly artificial intelligence, to significantly expand access to evidence-based mental health interventions. This role will apply clinical expertise, innovative thinking, and scientific rigor and will contribute directly to developing Lyra’s AI-powered tools. Lyra is at the forefront of increasing access to evidence-based, efficacious mental health services on a large scale by leveraging technology and clinical excellence. Lyra has developed innovative blended models of coaching and psychotherapy that combine leading clinical expertise with routine outcomes monitoring and engaging clinical tools. Scientific publications on Lyra’s mental health coaching, psychotherapy, medication management, and workforce mental health programs provide strong evidence for the clinical effectiveness of these programs. You will be part of a highly skilled and collaborative team with an established track record of cross-functional collaboration for the development of clinical technology in industry settings. By directly reaching millions of clients, your work will help create meaningful positive change on a large scale Responsibilities • Functioning at the intersection of clinical research, clinical expertise, and technological advancement in generative AI • Drawing upon rigorous clinical and scientific standards to inform and execute clinical AI development and evaluation methods • Leveraging clinical expertise and the latest science on evidence-based approaches to AI in mental health to inform clinical product development • Supporting AI-powered feature development across the product life cycle, including design and conceptualization, specifying requirements, evaluating feature performance, and monitoring post-deployment • Communicating clinical considerations and requirements to cross-functional teams and validating their integration • Collaborating extensively with cross-functional technical and clinical teams to achieve shared objectives • Staying informed of the latest developments in clinical AI research evidence and communicating insights to cross-functional partners Qualifications • PsyD or PhD in clinical psychology • Current clinical licensure is preferred • Strong foundational skills in clinical research methods and readily able to apply those methods to generative AI-focused work • 1+ year of experience with developing and/or evaluating digital mental health tools and interventions • Strong verbal and written communication skills, with an emphasis on communicating highly technical concepts to interdisciplinary and non-technical audiences • Strong interest in developing deep knowledge and skills in AI-related technical domains such as ML and prompt engineering • Prior experience in these areas is a plus • Excellent training in and deep understanding of evidence-based ment

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