Note: The job is a remote job and is open to candidates in USA. Curai Health is dedicated to transforming healthcare delivery through artificial intelligence and clinical expertise. They are seeking a Staff Applied AI Engineer to design, build, and ship machine learning and LLM systems that enhance clinician and patient interactions on their platform.
Responsibilities
- Define technical strategy across multiple AI initiatives, driving architectural decisions, influencing product and research direction, and aligning engineering investments across teams to maximize long-term business and clinical impact
- 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
Skills
- Bachelor's degree in Computer Science, Software Engineering, Math, or other related technical degree
- 5+ years of hands on engineering experience with 2+ years 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
- Comfortability working with messy, real-world data and designing evaluations to know whether a system is actually working
- Strong written and verbal communication; ability to cross-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
- 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
- Comprehensive medical, dental, and vision coverage
- Flexible spending plans
- Generous and flexible Paid Time Off (PTO), floating holidays, and parental leave
- 401k plan with employer matching
- 100% remote — work from home
Company Overview
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