Your mission
Build AI that runs in the real world. On real robots. Under real constraints.
At Autonomous Teaming, we build autonomous robotic systems operating in extreme, GPS-denied environments. Our models run fully on edge hardware (Jetson, FPGA, custom boards), with no cloud, no fallback, no excuses.
We’re looking for an engineer who loves hard problems : real-time inference, low-latency pipelines, CUDA kernels, TensorRT graphs, and deploying ML models directly on hardware.
If you enjoy debugging things that only break on the robot, this role is for you.
Missions :
Own the full pipeline from model to real-time inference on embedded devices:
- Optimize deep neural networks for Jetson, FPGA or ARM boards
- Apply quantization, pruning, distillation to hit strict FPS, power and memory budgets
- Convert & compile models using TensorRT, ONNX, CUDA, C++
- Build ROS nodes integrating optimized perception into the full robotic system
- Debug runtime failures, memory leaks, thermal throttling, kernel-level issues
- Benchmark and validate performance directly on hardware
- Ship models that run reliably in real-world, harsh environments