We're building foundation models for deploying general-purpose manipulation robots.
Our data infrastructure generates rich, multi-modal human demonstration data at exponential scale. We use it to train manipulation models that work reliably across tasks, objects, and robot embodiments. We are live in deployment across multiple verticals.\
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The robotics industry is focused on building bigger, more generalizable pre-trained models, but a robot has no commercial value unless it works 99% of the time. Our research is focused on answering how you get from 40% to 99% in real world deployments.
As founding engineer, you'll own the model pipeline end-to-end. You'll have $750K in compute credits across Azure, AWS, and GCP, NVIDIA Inception perks, and a bespoke data pipeline already running.
**What you'll do:**
* Own the train-test-deploy loop: curation, training runs, evaluation, deployment
* Select and tune architectures for our foundation model
* Collaborate with research organizations
* Set technical direction for the model team
**You should have:**
* Experience implementing models end-to-end on robots, or research experience in VLAs, world models, or imitation learning
* Proof of decision-making with incomplete information
* Extremely competitive nature
* No aversion to unglamorous work, in robotics, research and debugging have to go hand-in-hand
* A track record that shows you genuinely want to see robots deployed in the real world, projects, research, or competitions
Our culture is built on honesty and a willingness to fail fast. If you see yourself fitting here, please apply.
**Comp:**
* $80K-$200K
* 0.1%-2% equity
* Incredible office in NYC. Equipment budget, meals, etc.
Visa sponsorship is offered for this role.
