Who we are
Before the PC, there used to be a time where computing was locked inside big corporations. But thanks to hackers of Silicon Valley, everyone now has a computer and can develop for it.
The same should happen for robotics. We're building a platform that makes it accessible: the PC of robotics. An intuitive, open, affordable general-purpose robot for everyone.
If you're going to work on something crazy hard, it might as well matter. We're a small team that cares: about the problem, about the people using our robots, and about building a product that will still mean something years from now. We are our own users.
A robotics ML engineer with great engineering abilities; because a good ML system runs on solid engineering.
The core stuff that actually excites us:
ML research: you trained large models, and did proper research.
Multi-GPU optimization: you can do distributed training, inference optimization...
Network engineering: you know how to transmit data fast and efficiently.
Data pipelines: you've built ones in production.
Real robots: you worked with hardware before, and you liked it.
Robotics software systems: ROS, firmware, embedded code, the full stack.
Things that we prefer to see:
You've deployed in production and were personally responsible for it when it broke.
You've built something completely outside your main stack: a mobile app, a website, a side project that went somewhere. Builders want to build.
You know CI/CD, cloud deployment, and software update systems.
DO NOT censure yourself if you don't meet all of these requirements, we look for fast-learner more than anything else.
When something is wrong, you know which layer to look at before you've even started debugging. You've probably done something a little weird and you're proud of it. You have the most fun when doing something really hard.
When you apply, tell us about the weirdest or most unexpected thing you've built. That's the part we'll actually read first.
Training and deploying models that run on physical robots. Designing the infrastructure that makes that possible at scale. Think about and design the product, with the rest of the team, and stay close to customer's needs.
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