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2027 Internship Onboard Infrastructure Engineer, ML Inference

bedrock-roboticsSan Francisco, CAEngineering
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Salary
Not listed
Job type
Internship
Experience
Intern
Posted
10 Sept 2026
Status
Open · checked 7d ago

About this role

This internship suits a student currently pursuing a degree in Computer Science, Electrical or Computer Engineering, Robotics, or a related field who wants to gain hands-on experience in AI deployment. The 2027 Internship Onboard Infrastructure Engineer, ML Inference role is located in San Francisco, CA, and focuses on integrating machine learning models into autonomous heavy machinery.

Role Overview

As an Onboard Infrastructure Intern at bedrock-robotics in San Francisco, CA, the successful candidate works with the Onboard Infrastructure team to build the core engine of autonomous heavy machinery. The position involves integrating Large Language Models and Vision-Language-Action models into the core stack to operate within strict deadline budgets on edge compute.

Key Responsibilities

Integrate open-source and proprietary LLM and 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 for cameras and 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 inter-process communication using Nsight Systems, Nsight Compute, and eBPF.
Validate performance optimizations directly on heavy autonomous machinery at company test sites.

Requirements

Currently pursuing a Bachelor of Science, Master of Science, or Doctor of Philosophy in Computer Science, Electrical Engineering, 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 including multithreading, operating system and GPU scheduling, memory management, asynchronous programming, and inter-process communication.

Nice to Have

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

Skills and Tools

Rust
C++
PyTorch
JAX
CUDA
TensorRT
vLLM
ExecuTorch
ONNXRuntime
NVIDIA Jetson Thor
Nsight Systems
Nsight Compute
eBPF

About the Company

Bedrock Robotics is deploying autonomous systems on heavy construction equipment across the country to improve job site safety and accelerate schedules on critical infrastructure projects. The company has raised $350 million in two years and achieved the first fully autonomous excavator deployments in construction, featuring a team that includes veterans from Waymo, Segment, and Uber Freight.

How to Apply

Candidates should apply on the official company careers page.

Skills and tech stack

RustC++PyTorchJAXCUDATensorRTvLLMExecuTorchONNXRuntimeNVIDIA Jetson ThorNsight SystemsNsight ComputeeBPFLLMLLMs

Questions candidates ask

What is the location of the internship?

The internship is located in San Francisco, CA.

Who is eligible to apply for this internship?

Students currently pursuing a BS, MS, or PhD in Computer Science, Electrical/Computer engineering, Robotics, or a related field are eligible to apply.

What programming languages are required?

Proficiency in Rust or C++ is required, along with supporting experience in PyTorch or JAX.

What hardware and runtimes are used in the role?

The role involves working with NVIDIA Jetson Thor and tools like TensorRT, vLLM, ExecuTorch, Nsight Systems, and Nsight Compute.

How do I apply for the position?

Interested candidates should apply on the official company careers page.

Ready to apply?

The application is on the official bedrock-robotics careers page.

Apply on company site