Founding AI Research Scientist - Optexity (USA)

Job description

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