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Founding AI Research Scientist - Optexity (USA)
Pear-vc
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About this role
ABOUT OPTEXITY
Optexity is a product-driven research lab building clinical reasoning and computer use models on data no other lab can reach. We deploy directly inside clinics and hospitals — including systems with no APIs, using integration infrastructure we've built and open-sourced — and in return become their preferred partner. That gives us proprietary clinical reasoning trajectories from practicing physicians, and a feedback loop between real patient encounters, our models, and the products built on top of them.
We're a small, fast-moving founding team with multiple published papers in NeurIPS, ICML, CVPR etc and background from Apple, Amazon, Microsoft, CMU, IIT.
We are backed by world-class investors and leaders like Jeff Dean, Neotribe VC, PearVC, Together Fund and Zapier Fund.
HOW WE WORK
- Customer obsession — we start with the customer and work backwards
- Intellectual honesty — ideas matter more than titles; we communicate directly and assume good intent, even in disagreement
- Bias for action — we build and learn with customers rather than debate in the abstract
- Extreme ownership — we own outcomes, not just tasks, and see problems through
Why this role exists
Most research roles at this stage hand you a dataset everyone already has and ask you to be marginally better than the last person who tried. Here you get data nobody else has — real clinical reasoning trajectories from practicing physicians — and the room to figure out what to do with it. This is a founding research hire: you'll define the agenda as much as execute it, with direct founder access, real compute, and nothing between an idea and an experiment.
What you'll do
- Work with real, proprietary clinical data from hospital and clinic partners to surface insights that shape model and product direction
- Build clinical reasoning models that improve physician and clinic workflows
- Design and publish benchmarks that expose where current LLMs fall short on real clinical reasoning
- Evaluate computer-use models on real-world tasks
- Own the training and evaluation pipeline end to end
- Take open-ended problems from question to working model, with minimal predefined structure
- Write up findings as technical reports and papers
Ideal candidate
- Has real research experience — can define a problem, not just execute a known one
- Has trained models before (not just fine-tuned APIs) and is fluent in Python
- Master's or higher in ML or a related field
- Energized by open-ended problems and ambiguity
- Wants to publish, not just ship
- Takes ownership without needing to be guided
- Genuinely wants a startup over big tech — speed and ambiguity as defaults, not exceptions
Nice to have
- Prior founder or founding-engineer experience
- Strong product taste
- Worked on healthcare datasets before
- Built LLM-powered products before
- Ambitions to start your own company someday — we'll support that path
What you get
- Direct, daily work with the founders, plus exposure to board and investor conversations
- Real ownership of technical direction, with scope that grows as the company does
- Full compute and data to do the work properly
- Competitive salary and meaningful equity
- Visa sponsorship available
Salary insight
This posting doesn't disclose pay. Across 6,783 San Francisco jobs with disclosed salaries on ForgeApply, the median is $200k.
Based on live postings with disclosed pay on ForgeApply; refreshed daily. Not an estimate of this employer's offer.
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