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Internship 2027 Onboard Infrastructure Engineer, ML Inference at Bedrock Robotics · LumiJobs

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Bedrock Robotics· Posted Sep 10, 2026

Internship 2027 Onboard Infrastructure Engineer, ML Inference

San Francisco, CA · Remoteinternship

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Remote

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H1B: no

Bedrock Robotics Internship role as Onboard Infrastructure Engineer focusing on integrating LLM and VLA models into real-time autonomous machinery control systems. Responsible for profiling and optimizing model execution on edge compute platforms.

Responsibilities

The Onboard Infrastructure team builds the core engine of Bedrock’s autonomous heavy machinery — where safety, real-time control, and millisecond-level responsiveness are non-negotiable. As an Onboard Infrastructure Intern, you will bridge frontier AI and real-time execution by integrating Large Language Models (LLMs) and Vision-Language-Action (VLA) models into our core stack, ensuring multi-billion parameter multi-modal models run within strict, deterministic deadline budgets on edge compute.
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.

Qualification

Currently pursuing a BSProficiency in Rust or C++Solid foundation in GPU architecturesAbout This InternshipThis is a fixed-termReasonable Accommodations

Required

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.

Preferred

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.
About This Internship
This is a fixed-term, project-based internship designed strictly for students (undergraduate or graduate) seeking resume-building experience, hands-on skill development, or industry exposure rather than a direct career launchpad. Candidates will own discrete, short-term projects that can be fully completed within the internship timeframe. Please note that while exceptional interns may occasionally be considered if business needs align, opportunities for full-time conversion are highly limited."
Bedrock Robotics is an Equal Opportunity Employer
We’re committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, veteran status, genetic information, or any other protected characteristic.
Reasonable Accommodations

Benefits

Vision

Company

Bedrock Robotics

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Source: ashby

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Remote-friendly

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Must-Have Skills for This Role

RustC++PytorchJAXTensorRTvLLM

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