We're hiring a researcher/engineer to solve deep AI challenges.
Join us in building state-of-the-art agent systems for previously unsolved domains. You'll work on diverse AI challenges that push the boundaries of what's possible with current models.
Work on building and constantly improving a SOTA Agent for our domain
Design robust learning pipelines (e.g. RLHF, RL) and build any custom environments needed for feedback signal
Set up a durable eval strategy
Train smaller models for scoped tasks
Leverage a variety of open source text and image models
Stay abreast of research — we will have budget for you to attend conferences
Shape our technical and hiring strategy alongside the founding team
Have experience with AI agents, RLHF or reinforcement learning (even in academic projects/internships)
Are extremely comfortable in Python and ML frameworks
Have a builder mindset, whether through research projects, internships, side projects, or production systems
Can make independent progress on shipping user-facing features
(Bonus) Have an advanced degree
(Bonus) Have started a company or been early at a startup
A note on seniority: We believe in slope over y intercept, and are open to a broad range of experiences and seniority.
Learning & Growth: Direct mentorship from founders who've built Dover (raised $23M) and Heap ($960M valuation, acquired). You'll learn how to build and scale transformative products from people who've done it.
Impact: The team is small and will stay small. We aspire to a very high revenue to headcount ratio. Every engineer directly shapes the product and company trajectory. No layers, no politics, just building.
Ownership: We're a high-trust environment where you'll own significant projects from day one, with support when you need it.
Ambition: We're redefining who can use design tools and how they work, with a massive potential audience and the technical challenges to match.
Speed: We move incredibly quickly. You'll ship more in a month here than most engineers ship in a year.