Software Engineer

About the CompanyThe 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.About the roleWe'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.ResponsibilitiesShip performance-critical code to real robots dailyLearn the full data flow: camera frames in, perception and planning in the middle, control commands and actuator feedback out, and the systems that carry themContribute to the real-time control loop: help keep high-rate control running deterministically alongside vision inferenceBuild pieces of the perception data path: move high-bandwidth camera streams into the CV and ML models with minimal latency and zero silent dropsPush down latency and tighten the stack to make the system faster, more deterministic, and more reliableBring visibility into the pipeline: build tooling and instrumentation that make real-time behavior across controls and vision observable and debuggableMinimum Qualifications1+ 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 multithreadingExperience building things: production systems, internal tools, student teams, or personal projects that workedDebugged real timing, concurrency, or hardware issues, even in a project settingComfort with ambiguity and a strong learn-by-doing instinctAble to work on-site in San Francisco 5 days/week (6 days/week if needed during crunch time), embedded in the teamPreferred QualificationsLinux kernel or embedded systems experienceExposure to build and test infrastructure: Bazel, Nix, HIL testing, or CI/CDExperience with real-time control systems: motor control, high-rate control loops, or robot controllersComputer vision pipeline experience: camera drivers, image transport, GPU inference, or sensor synchronizationTracing and profiling experience: ftrace, flamegraphs, eBPFComfort using AI tools to multiply your own output