Bot Auto
GPU Engineer
About this role
Bot Auto seeks a GPU Engineer to optimize high-performance computing for autonomous driving systems. You'll work on real-time inference, sensor processing, and GPU-accelerated software for embedded platforms, collaborating with AI researchers and hardware teams.
What you'll do
- Optimize GPU performance for autonomous driving workloads including sensor processing and neural network inference
- Develop and optimize parallel computing algorithms using CUDA and other GPU technologies
- Design onboard GPU software architectures for perception, planning, and control modules
- Profile and analyze GPU bottlenecks in computation, memory, and CPU-GPU interaction
- Debug and optimize GPU software for latency, throughput, and resource utilization on embedded systems
What they're looking for
- CUDA and parallel computing
- GPU architecture and performance optimization
- C/C++ and Python
- PyTorch, ONNX, TensorRT
- NVIDIA Nsight Systems and Compute profiling
- Real-time embedded systems
- Sensor data processing (camera, LiDAR, radar)
- Neural network inference optimization
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Bot Auto
Bot Auto builds autonomous truck technology, developing the mechanical systems, deep learning models, and operational software that power self-driving commercial freight vehicles. The company is hiring mechanical engineers, machine learning engineers, software engineers, and interns to work across hardware design, perception and control systems, ML infrastructure, and fleet management platforms.
View all jobs at Bot AutoLikely interview questions
- Walk us through your experience optimizing GPU kernels for latency-critical applications—what profiling tools did you use and what bottlenecks did you identify?
- Describe a time you optimized neural network inference on embedded GPUs. What frameworks did you use and what performance improvements did you achieve?