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Civ Robotics inc. in San Francisco is seeking a Physical AI Engineer to explore, prototype, and deploy intelligent systems on real robots. The role focuses on learning-based perception, vision systems, and combining classic robotics with modern ML techniques.
You will work with autonomy, controls, embedded, mechanical, and product engineers to advance the next generation of physical AI architectures. This is an in-office, full-time position at staff level.
Physical AI Engineer
San Francisco
Engineering
In office
Full-time
Civ Robotics is on a mission to automate repetitive tasks within the $3 trillion infrastructure construction industry. We’re dedicated to bridging the workforce gap and accelerating the development of essential infrastructure projects. At the core of our mission is our innovative technology in robotics and autonomous navigation.
With over 100 robots deployed and operating across construction sites worldwide, we pride ourselves in ushering in the next generation of construction layout tools for solar, civil, land surveying, road striping, and general contracting. Our technology is engineered from the ground up to make our customers’ projects more precise, simple, and efficient than ever before.
Join us and become an integral member of our dynamic team, leading the charge in pioneering construction robotics innovation!
You’ll explore, prototype, and deploy new approaches to intelligence on real robots.
That could mean:
At Staff level, you’ll also help identify what we should be working on next - not just execute an existing roadmap.
You have deep experience in some combination of:
But more importantly, you know how to make things work outside the lab.
You understand that a model running once in a notebook is very different from a model running every day on a robot.
You care about latency, compute, bad sensors, weird edge cases, changing environments, debugging, and the thousand small details between a good idea and a working machine.
Experience with any of the following is useful, but not required:
We have something that is still rare in Physical AI: Real robots, doing real work, generating real data.
Our machines are deployed in environments where autonomy creates immediate economic value. That gives us the opportunity to close the loop between deployment, data, learning, and improvement.
You’ll be able to build something, put it on a robot, test it in the field, learn from it, and make the next version better.
We’re looking for someone who wants to help figure out what the next generation of real-world robots should look like and then build it.