2027 Internship Onboard Infrastructure Engineer, ML Inference
San Francisco, CAInternPosted 1mo ago
About the role
Onboard Infrastructure Intern focused on integrating LLM/VLA models into Bedrock’s onboard Rust middleware for autonomous heavy machinery, optimizing real-time model execution on edge hardware and ensuring deterministic performance.
Responsibilities
- Integrate open-source and proprietary LLM/VLA models into the onboard Rust middleware stack alongside perception, planning and control pipelines.
- Profile and optimize model execution using TensorRT, vLLM, ExecuTorch or custom edge inference runtimes tailored for NVIDIA Jetson Thor.
- Streamline sensor tokenization (cameras, LiDAR) to feed real-time streams directly to models without latency spikes in vehicle control loops.
- Identify and eliminate bottlenecks across memory bandwidth, compute, and IPC using tools like Nsight Systems, Nsight Compute and eBPF.
- Validate performance optimizations directly on heavy autonomous machinery at test sites.
Qualifications
- Currently pursuing a BS, MS, or PhD in Computer Science, Electrical/Computer engineering, Robotics or a related field.
- Proficiency in Rust or C++, with supporting experience in PyTorch or JAX.
- Solid foundation in GPU architectures, CUDA, or parallel computing.
- Understanding of modern systems concepts: multithreading, OS and GPU scheduling, memory management, asynchronous programming and IPC.
Skills
Required:Rust or C++GPU architectures / CUDAMultithreading / IPC / OS scheduling
Nice to have:TensorRT / ONNXRuntime / ExecuTorch
Last updated Oct 15, 2026. Interested? Apply on the company site.
About Bedrock Robotics
Advanced Autonomy for the Built World
Advanced Autonomy for the Built World
AutonomyBedrock Operatorautonomyheavy machineryindustrial automationindustrial roboticsmachine intelligenceon-site autonomy
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