AI Research Intern - Optexity (USA)
Pear VC
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