Member of Technical Staff, AI/ML

🕒 May 22

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Curai Health

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

⚕️ Healthcare Insurance

💰 $27.5M Series B on 2020-12

Artificial Intelligence • Healthcare Insurance

Curai Health is a company that provides comprehensive virtual primary care solutions integrating artificial intelligence with medical professionals' expertise. The company aims to expand access to cost-effective primary care through AI-assisted technology, promoting better patient outcomes and increased healthcare equity while reducing operational costs. Curai Health supports health plans, health systems, and third-party administrators by embedding AI-enhanced software and care teams to optimize care delivery and patient management. Their platform facilitates personalized primary care, urgent care, prescription and lab ordering, condition management, network navigation, and clinical workflow integrations, all aiming to enhance patient experience and healthcare reach. Curai Health is committed to using AI substantively to improve healthcare efficiency and effectiveness, setting it apart as a partner for organizations aiming to enhance their virtual care capabilities.

📋 Description

• Design, build, train, evaluate and improve advanced machine learning and LLM-based systems for patient and provider-facing products (e.g., conversational AI, personalization, user understanding, clinical decision support, chronic care management). • Own problems end-to-end: scope the problem with clinicians and product partners, build datasets and evaluations, iterate on modeling, and ship to production with the right monitoring and guardrails. • Develop robust evaluation frameworks — offline benchmarks, human-in-the-loop review, online experiments — that give us confidence our models are safe, accurate, and improving over time. • Build and improve the platform that lets the team move quickly: data pipelines, training and inference infrastructure, prompt and model management, and tooling for clinical reviewers. • Partner closely with clinicians, product, and engineering to translate medical and operational requirements into ML problems and ship measurable improvements to patient and clinician experience. • Set technical direction for your area, mentor other engineers, and raise the bar on engineering and scientific rigor. The scope of leadership scales with seniority. • Stay close to the literature and the rapidly evolving AI ecosystem; bring back what is most useful for our patients and our team.

🎯 Requirements

• Hands-on experience building and deploying machine learning systems including generative AI (LLMS) , — and a clear track record of impact. • Strong software engineering fundamentals and the ability to ship reliable, well-tested code in Python (or a comparable language) in a production environment. • Practical understanding of modern LLM techniques: prompting, retrieval-augmented generation, fine-tuning, evaluation, and the trade-offs between them. • Comfort working with messy, real-world data and designing evaluations to know whether a system is actually working. • Strong written and verbal communication; ability to collaborate with clinicians, product managers, and engineers across disciplines. • A bias toward action and ownership: you can take an ambiguous problem, drive it to a result, and bring others along. • Care for the mission. You want your work to translate into better health outcomes for real patients. • Nice to have • Experience applying ML or LLMs in healthcare, life sciences, or another regulated, high-stakes domain. • Experience with clinical NLP, medical knowledge representation, or working with electronic health record data. • Experience building agentic systems, tool-using LLMs, in production. • Experience scaling ML infrastructure — training pipelines, distributed inference, evaluation platforms — for a small, fast-moving team. • Track record of technical leadership: setting direction across teams, mentoring engineers, or publishing influential work.

🏖️ Benefits

• High ownership work on problems that matter, with a tight feedback loop from real clinicians and patients. • A small, senior team where your work shows up in the product quickly. • Competitive compensation, meaningful equity, and comprehensive benefits. • Remote-first, flexible work environment across the U.S.