AI Research Intern - Optexity

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