{"slug": "internship-2027-onboard-infrastructure-engineer-ml-inference-bedrock-robotics", "title": "Internship 2027 Onboard Infrastructure Engineer, ML Inference — Bedrock Robotics", "summary": "Bedrock Robotics posted an internship opening for a 2027 Onboard Infrastructure Engineer, ML Inference role based in San Francisco, CA, on a hybrid schedule, with pay not published. The intern will integrate open-source and proprietary LLM and Vision-Language-Action models into Bedrock's onboard Rust middleware and optimize execution using TensorRT, vLLM, ExecuTorch or custom edge inference runtimes on NVIDIA Jetson Thor. Bedrock Robotics states it has raised $350M in two years and achieved the first fully autonomous excavator deployments in construction.", "body_md": "# Internship 2027 Onboard Infrastructure Engineer, ML Inference\n\n- Salary\n- Not published\n- Location\n- San Francisco, CA\n- Work type\n- Hybrid\n- Level\n- Intern\n- Posted\n- today\n- Verified live\n- today\n\n[Apply on company site (opens in new tab)](https://jobs.ashbyhq.com/bedrock-robotics/0331551e-c18e-428a-8e91-e6cb25c9c2e8/application)\n\nFiled under[LLM Engineer](/llm-engineer-jobs/)[Inference / Serving](/inference-engineer-jobs/)[Core ML](/machine-learning-engineer-jobs/)\n\n507 of 653 [Core ML roles in the United States on this board](/machine-learning-engineer-jobs/) publish pay; their median is **$238k**.\n\nJoin the team bringing advanced autonomy to the built world\n\nAt Bedrock, we're 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, we're deploying autonomous systems on heavy construction equipment across the country, improving safety on job sites and accelerating schedules on critical infrastructure projects.\n\nWe're not here debating the future of AI. We're deploying it in the real world. In just two years, we've raised $350M and achieved the first fully autonomous excavator deployments in construction.\n\nThis is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us.\n\nAbout the Role & Team\n\nThe 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.\n\nWhat You'll Do\n\n- Integrate open-source and proprietary LLM/VLA models into our onboard Rust middleware stack alongside existing perception, planning and control pipelines.\n- Profile and optimize model execution using TensorRT, vLLM, ExecuTorch or custom edge inference runtimes tailored for NVIDIA Jetson Thor.\n- Streamline sensor tokenization (cameras, LiDAR) to feed real-time streams directly to models without latency spikes in vehicle control loops.\n- Identify and eliminate bottlenecks across memory bandwidth, compute, and IPC using tools like Nsight Systems, Nsight Compute and eBPF.\n- Validate your performance optimizations directly on heavy autonomous machinery at our test sites.\n\nWhat We're Looking For\n\nRequired\n\n- Currently pursuing a BS, MS, or PhD in Computer Science, Electrical/Computer engineering, Robotics or a related field.\n- Proficiency in Rust or C++, with supporting experience in Pytorch or JAX.\n- Solid foundation in GPU architectures, CUDA, or parallel computing.\n- Understanding of modern systems concepts: multithreading, OS and GPU scheduling, memory management, asynchronous programming and IPC.\n\nBonus Points\n\n- Practical experience deploying neural networks on constrained hardware using TensorRT, ONNXRuntime or ExecuTorch.\n- Experience with LLM/VLA optimization techniques such as KV-cache management, FP8/INT4 quantization, continuous batching or speculative decoding.\n- Exposure to multi-modal/VLA models or robotics frameworks.\n\nBedrock Robotics is an Equal Opportunity Employer\n\nWe’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.\n\nReasonable Accommodations\n\nWe 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.", "url": "https://wpnews.pro/news/internship-2027-onboard-infrastructure-engineer-ml-inference-bedrock-robotics", "canonical_source": "https://frontierroles.com/jobs/bedrock-robotics-internship-2027-onboard-infrastructure-engineer-ml-inference-17c7d8/", "published_at": "2026-09-10 21:22:05+00:00", "updated_at": "2026-09-11 03:57:54.323149+00:00", "lang": "en", "topics": ["ai-products", "robotics", "large-language-models", "ai-infrastructure", "ai-chips"], "entities": ["Bedrock Robotics", "NVIDIA Jetson Thor", "TensorRT", "vLLM", "ExecuTorch", "Waymo", "Segment", "Uber Freight"], "alternates": {"html": "https://wpnews.pro/news/internship-2027-onboard-infrastructure-engineer-ml-inference-bedrock-robotics", "markdown": "https://wpnews.pro/news/internship-2027-onboard-infrastructure-engineer-ml-inference-bedrock-robotics.md", "text": "https://wpnews.pro/news/internship-2027-onboard-infrastructure-engineer-ml-inference-bedrock-robotics.txt", "jsonld": "https://wpnews.pro/news/internship-2027-onboard-infrastructure-engineer-ml-inference-bedrock-robotics.jsonld"}}