Founding Research Engineer

Nollahealth
New York, NY
On-site

Who this role is best for

Aimed at mid-to-senior level engineering researchers who can build and lead clinical evaluation systems.

Best fit for

  • Candidates with experience in building evaluation infrastructure for AI systems
    — “You have built eval infrastructure for LLM systems that other people depended on”
  • Individuals who have led research projects from concept to publication
    — “You can write a paper. Authorship on empirical ML work, ideally with a human comparison or a benchmark release”
  • Candidates excited about clinical AI and bridging human expertise with machine learning
    — “You are excited to work with some of the best physicians in the country and turn their judgment into model performance”

Things to consider

  • The role demands immediate patient impact and high collaboration with clinicians
    — “Your work reaches patients immediately. This is a hands-on role: you will write code most days, design studies”
  • The position requires in-person presence in New York City
    — “Work Setup: In-person, New York City”

How to stand out

  • Highlight experience with clinical evaluation frameworks and benchmarking systems
    — “Design and maintain the benchmarks we use to judge clinical accuracy, safety, and documentation quality”
  • Showcase prior work in integrating clinician feedback into model training
    — “Turn real, consented cases into eval cases and training examples, with clinician review”
  • Emphasize leadership in research projects, especially those involving publication
    — “Lead our clinical evaluations from protocol through publication”
Pace · Fast PacedCollaboration · MediumAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • state-of-the-art clinical models
  • published benchmarks
Typical background
AI researchclinical evaluation

Skills & requirements

Required

AI EvaluationClinical BenchmarksLLM SystemsPost-training

Preferred

Multimodal ModelsAgentic Clinical Benchmarks

Stack & domain

AI SystemsClinical BenchmarksLLM SystemsData CurationCommunicationTeamworkProblem SolvingAIHealthcare

About the role

Original posting from Nollahealth via Ashby

THE MISSION

Nolla is building AI doctors so that top-quality healthcare is accessible to everyone. Nolla Derm is the #1 medical skincare treatment app in the U.S. App Store. We've treated thousands of acne patients in the U.S., scanned 1% of Norway's population for skin cancer, and our in-house clinical models are state of the art on clinical benchmarks. We just launched NollaMD, our urgent care app, and we're building dedicated specialty apps for conditions like women’s health. We’ve raised $6.5M from General Catalyst and other strategic investors.

THE ROLE

We have built our own clinical benchmarks, post-trained on them, and produced models that beat frontier performance on clinical tasks. We are in a unique position of both delivering care to real patients and training the models that deliver it. You’ll work on our evals and harnesses, build the data loop with clinicians that feeds them, and lead where they go next.

You'll work directly with the founding team and with our post-training partners, and your work reaches patients immediately. This is a hands-on role: you will write code most days, design studies, and be the author of record on what we publish.

WHAT YOU'LL BUILD

EVALS AND BENCHMARKS

  • Design and maintain the benchmarks we use to judge clinical accuracy, safety, and documentation quality
  • Extend them to our agentic system: tool use, long-horizon tasks that span many visits, memory of a patient's history, uploaded records, labs, and escalation behavior

GRADERS AND HARNESSES

  • Build the grading stack: deterministic checks, rubric graders, and LLM judges calibrated against clinician ratings
  • Improve the production harness the product runs on

DATA LOOP WITH CLINICIANS

  • Turn real, consented cases into eval cases and training examples, with clinician review, de-identification, and provenance built in
  • Run the clinician review workflows that produce rubrics, labels, and feedback at scale

RESEARCH

  • Lead our clinical evaluations from protocol through publication, and publish our benchmarks for the field
  • Collaborate with post-training on reward design and data curation, and run experiments where it helps

WHAT YOU BRING

  • You have built eval infrastructure for LLM systems that other people depended on
  • You have opinions about contamination, difficulty calibration, judge bias, and reward hacking
  • You can write a paper. Authorship on empirical ML work, ideally with a human comparison or a benchmark release
  • You are excited to work with some of the best physicians in the country and turn their judgment into model performance
  • You've worked on small teams and built things from zero

BONUS POINTS

  • Clinical AI evaluation experience: rubric-based health benchmarks, simulated-patient studies, agentic clinical benchmarks
  • Post-training experience (RLHF, DPO, GRPO or similar)
  • Experience with multimodal models
  • Familiarity with eval and environment frameworks such as Inspect, Verifiers, or Harbor

ROLE LOGISTICS, COMPENSATION & BENEFITS

  • Role Type: Engineering
  • Salary: $180,000–$240,000, based on experience
  • Job Type: Full-time
  • Work Setup: In-person, New York City
  • Equity: Meaningful equity, commensurate with experience
  • Health Insurance: Medical, dental, and vision
  • HSA/FSA: Eligible
  • Time Off: Flexible, unlimited vacation
  • Additional Perks: Meal stipends, team retreats
  • Work Hours: Flexible but demanding. We're building something that matters
  • Growth: Founding team members step into expanded roles as we scale

Source: Nollahealth careers (Ashby)

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