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Robots and world models learn about the physical world from video: millions of hours of people cooking, building, carrying and fixing things. That footage is piling up faster than anyone can review it, and much of it is mislabeled, out of sync or not useful for training. Most teams still choose what to train on by having people watch a small sample. When a model learns from bad examples, it learns the wrong behavior.
Eventual is building data curation for Physical AI. We process video and sensor data at petabyte scale and extract signals from it: how hands and objects interact, what happens over time (a failed grasp, a retry, a recovery) and whether a clip is reliable enough to learn from. Leading Physical AI labs and robotics teams use these signals to decide what goes into their next training run.
The work spans large-scale data systems, computer vision and ML research, and it ships directly into how frontier models get trained. We’re a small team from AWS, Lyft and Tesla, backed by $30M from Felicis, CRV, Y Combinator and the co-founders of Databricks and Perplexity. We helped power the last generation of Physical AI in self-driving, and now we’re building what the next generation trains on.
Join our small (but powerful!) team, 4 days/week in our SF Mission District office.
As Chief of Staff, you’ll own the work that decides how fast Eventual grows and doesn’t belong to any one function. We’re a small team selling infrastructure to some of the most demanding engineering organizations in the world — Physical AI labs, AV programs, GPU cloud providers — and at our size a customer conversation becomes a contract question, a contract question becomes a pricing decision, and a pricing decision becomes a hiring plan. Someone has to carry that thread end to end.
You’ll own the company’s operating cadence — planning, metrics, board and investor materials — and step into whatever sits between teams: customer and partner conversations, contracts and legal, hiring, and the projects that don’t have an owner yet. This is a generalist role — meaning you’ll move between go-to-market, operations, and legal in the same week, but you own the outcomes and execute on them.
The functions you build here will eventually have leaders of their own. Build one well, and the most likely outcome is that you run it.
Own the operating cadence end-to-end: planning, company goals and metrics, board and investor materials, and the written decisions that keep a small team pointed in the same direction.
Sit in on customer, partner, and GPU cloud conversations with the CEO — and run them yourself when the CEO can’t — carrying each to an outcome rather than a summary.
Step into the functional seat we haven’t hired yet, whether that’s sales or marketing in a given quarter, then build the motion behind it so the eventual hire inherits a system instead of anecdotes.
Own contracts and the legal path: act as the internal counterpart to outside counsel and carry deals through procurement and security review so engineers stay on product.
Pick up the ambiguous cross-functional problem — pricing, a partner program, the first go-to-market hires — drive it to a decision, and hand it off or hire against it, complementing our business operations function rather than duplicating it.
2-5 years of high-ownership work — Chief of Staff, business operations, strategy and operations, or early go-to-market at a startup, or consulting, banking, or VC followed by an operating role. A degree in a quantitative, technical, or business field is common on this path.
Broad operating range across planning, metrics, contracts, vendors, and hiring, and comfort moving between them in a single day.
Comfortable with commercial and legal detail — you can read an MSA, work with outside counsel, and hold your own on a customer or partner call.
Clear writing and clear thinking — your memos and decks are good enough to send as-is, and a vague problem comes back from you as a recommendation.
Technically literate enough to follow what our engineers are building and explain it to a customer. You don’t need to write code.
Time at a data infrastructure, developer tools, or AI infrastructure company, or familiarity with the GPU cloud ecosystem.
Exposure to Physical AI — autonomous vehicles, robotics, or ADAS — and a sense of what those teams work on day to day.
Experience taking open source to a commercial business, or developer marketing, launches, and events you ran yourself.
Enterprise procurement and security reviews, or a Series A or B raise you helped run from the inside.
A bachelor's degree, or higher, in business administration, management, or a related field
In-person, tight-knit team — 4 days/week in our SF Mission office.
Competitive comp and meaningful startup equity.
Catered lunches and dinners for SF employees.
Commuter benefit.
Team-building events and poker nights.
Health, vision, and dental coverage.
Flexible PTO.
Latest Apple equipment.
401(k) plan with match.