Internship 2027 Onboard Infrastructure Engineer, ML Inference

Bedrock Robotics develops autonomous systems for heavy construction equipment and deploys advanced AI in real-world environments. The Onboard Infrastructure Intern will integrate and optimize LLM and VLA models within the company’s Rust-based onboard middleware, ensuring real-time performance on edge hardware and validating improvements on autonomous machinery.

What you'll do:

• Integrate open-source and proprietary LLM/VLA models into our onboard Rust middleware stack alongside existing 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 your performance optimizations directly on heavy autonomous machinery at our test sites

What they're looking for:

• 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
• Practical experience deploying neural networks on constrained hardware using TensorRT, ONNXRuntime or ExecuTorch
• Experience with LLM/VLA optimization techniques such as KV-cache management, FP8/INT4 quantization, continuous batching or speculative decoding
• Exposure to multi-modal/VLA models or robotics frameworks

Benefits:

• Hybrid work arrangement