2027 Internship Onboard Infrastructure Engineer, ML Inference

Join the team bringing advanced autonomy to the built world

At Bedrock were moving AI out of the lab and into the real world. Our team includes veterans who helped launch Waymo scaled Segment to a $3.2B acquisition and grew Uber Freight to $5B in revenue. Today were deploying autonomous systems on heavy construction equipment across the country improving safety on job sites and accelerating schedules on critical infrastructure projects.

Were not here debating the future of AI. Were deploying it in the real just two years weve raised $350M and achieved the first fully autonomous excavator deployments in construction.

This is where algorithms meet steel-toed boots. Youll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations cant touch. If youre ready to do meaningful work on hard problems wed love to have you join us.

About the Role & Team

The Onboard Infrastructure team builds the core engine of Bedrocks 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.

What Youll 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 Were Looking For

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.

Bonus Points

• 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.

Bedrock Robotics is an Equal Opportunity Employer

Were 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

We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process please let your recruiter know so we can support you.

Required Experience:

Intern