Gradient Robotics is building autonomous robots for AI infrastructure buildout. Backed by South Park Commons.
About the role
We're looking for a Software Engineer to help move data from AI models to actuators. You'll work close to the hardware, from kernel and firmware up through the controls and perception layers, contributing to real-time pipelines that move hundreds of megabytes at single-digit millisecond latency. Vision inference, control loops, and actuation all live on the same clock, and you'll help keep them there.
What they're looking for
- 1+ years of software engineering experience building systems close to hardware (exceptional new grads with strong project or internship experience are welcome to apply)
- Strong programming fundamentals in at least one of Rust, C++, or Python, with solid understanding of operating systems and multithreading
- Experience building things: production systems, internal tools, student teams, or personal projects that worked
- Debugged real timing, concurrency, or hardware issues, even in a project setting
- Comfort with ambiguity and a strong learn-by-doing instinct
- Able to work on-site in San Francisco 5 days/week (6 days/week if needed during crunch time), embedded in the team
More about this role
The datacenter buildout is the largest industrial project in human history. Gradient builds the autonomous robots that make it possible.
Partnered with the world's largest AI infrastructure companies and backed by the industry's best investors, we move fast and build full-stack systems that matter.
We're looking for a Software Engineer to help move data from AI models to actuators. You'll work close to the hardware, from kernel and firmware up through the controls and perception layers, contributing to real-time pipelines that move hundreds of megabytes at single-digit millisecond latency. Vision inference, control loops, and actuation all live on the same clock, and you'll help keep them there. The goal: bring visibility and determinism into the end-to-end inference pipeline so the ML model is the only stochastic component. We iterate fast (multiple robot generations in months, not years), so the code you ship lands on real machines doing real precision work almost immediately.
Ship performance-critical code to real robots daily
Learn the full data flow: camera frames in, perception and planning in the middle, control commands and actuator feedback out, and the systems that carry...
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