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Introduction
We work with frontier labs, hyperscalers, and enterprises to help develop and deploy the next generation of embodied agents. We see the creation of evals and environments, codifying human goals for agents, as the highest leverage human activity in the build up to ASI.
We’ve raised from Sequoia Capital, Menlo Ventures, and SV Angel, are growing very quickly, and are off to the races to build the core infrastructure to unlock double digit economic growth with the next generation of agents.
A Brief Description of the Role
As Member of Technical Staff, Data, you will own our real world and synthetic data pipelines as well as closely collaborate with our team and frontier research labs to develop realistic scenarios & simulations for agents. We are looking for high-agency deeply technical candidates that work fast, are able to effectively delegate work to fleets of coding agents, and have a deep understanding/appreciation for AI research and low-level infrastructure.
You will work at the frontier of AI development every single day servicing some of the smartest people in the world on a problem that, if solved, will be among the biggest unlocks to double-digit economic growth.
You will not be a good fit if you:
- Thrive in routine, consistency, or structure, or you value planning and aren’t good at context switching between tasks or priorities.
- Alternatively, we are looking for people who are excited to work on the frontier which is (almost by definition) filled with ambiguity and chaos.
- Think in dev cycles on the scale of weeks or months, expect long planning cycles, and require sufficient notice to change course.
- Alternatively, we are looking for people that are excited to ship in the matter of days, and will stop at nothing to make it happen.
- Are primarily motivated by specific technical challenges and want to primarily spend your days focusing on one thing that excites you.
- Alternatively, we are looking for people that aren’t afraid to get their hands dirty and are excited to do a bit of everything across the entire tech stack, and across engineering and non-engineering work. We are looking for people that will stop at nothing to make the business succeed.
- Don’t use AI, or aren’t excited to spend a lot of time communicating clearly and effectively to AI agents.
- Alternatively, we are looking for people that are good at delegating and managing many AI agents in parallel, are able to keep that context in your head.
- Get things done for the sake of getting them done, or are fast and scrappy without care or focus on detail.
- Alternatively, we are looking for people that don’t sacrifice quality for speed; they deeply care about the work they put out, and therefore are incredibly fast but maintain the consistency and the quality as they work.
We don’t care about background, experience, or prestige. We want people that can demonstrate that they will work hard, learn fast, and understand at least one of {AI research, low-level infrastructure, AI agent engineering} deeply.
Former founders, early engineers at early-stage startups, and AI research experience is a plus.
We are on-site in San Francisco, CA. Compensation (salary + equity) will be extremely competitive.
A Brief Description of Us
Being an engineer at an early-stage startup is not easy. Here are some of our values and what we care about. If this excites you, we would love to chat.
- Own their outcomes: We succeed when our partners succeed. Therefore, we listen, build trust, and deliver value beyond what is contracted. We develop novel environments to study AI safety and capabilities. We post-train our own agents to share our learnings and best-practices. We study model behavior intensely and frequently report observations in our initial evaluation runs.
- Relentlessness: We are relentless in the speed at which we move when we build conviction, in getting in front of the right people, and in improving ourselves as a company and as individuals.
- Truth over comfort: Integrity to us means being honest with our partners, each other, and most importantly, ourselves. At the end of the day, early-stage startups are about the relentless pursuit of the truth, and we hold ourselves to a high standard to ensure we live that and succeed.
- Precision under pressure: We care deeply about delivering infrastructure to train safe, reliable agents. As such, a single detail in an environment can be the reason for unintentional failures within major training runs. Everyone on the team is fast and scrappy, but pays attention to every small detail. We don’t cut corners; we cut scope.
- Grit: A startup is built by people who like to get their hands dirty. We want to see that when left to your own devices, you know what to do and can stay resilient in the face of uncertainty and ambiguity.