Join us at Bedrock Robotics

Bedrock is bringing autonomy to the construction industry! We’re a group of veterans from the autonomous vehicle industry who are passionate about bringing the benefits of automation to areas in the construction industry currently underserved by the market. We’re looking for a highly motivated engineer with experience deploying machine learning algorithms to physical systems in the real world. The ideal candidate has hands-on experience in perception (e.g., object detection, semantic segmentation, depth estimation) and/or behavior learning methods (e.g., Vision-Language-Action (VLA) models, diffusion policies). More importantly, you’ve shipped ML models to robots in production environments, and you understand the complexities that come with it. What you’ll do: Develop and optimize real-time ML models for edge deployment on robotic systems Work with vendors to label data and build robust data extraction and labeling pipelines Design custom metrics to evaluate model performance in the field Reduce model latency using tools like ONNX, TensorRT, or similar What we’re looking for: Practical experience applying machine learning with deep learning frameworks, such as PyTorch, to solve real-world problems Proficiency in Python and comfort with at least one systems language (e.g., C++, Rust) Experience deploying ML models to robotic systems or other physical platforms Experience incorporating raw sensor data like camera, lidar, radar, IMUs, etc into deep learning algorithms. Bonus: Practical application of incorporating 3D geometry into deep learning models Bonus: Published work in conferences such as ICRA, IROS, CoRL, CVPR, ECCV, ICCV, ICML, NeurIPS, ***We’re especially interested in engineers who thrive at the intersection of ML research and real-world robotics applications.  

The Role The Onboard Infrastructure team is responsible for the base platform software and middleware running on our onboard computer and safety controller. From board bring-up through application development, we build our entire stack in Rust. We are looking for a Senior or Staff Software Engineer to join our team to architect, develop, and optimize the base software for our onboard autonomy computer, ensuring our autonomy stack has a secure, deterministic, and highly optimized foundation to run on. In this role, you will: Architect and maintain the embedded Linux stack for our NVIDIA Jetson platform, including board bring-up, kernel configuration, and OS customization. Develop and optimize low-level drivers, including for high-bandwidth sensors such as cameras and lidars, ensuring low-latency and low-overhead data ingestion. Implement system services such as OTA software updates, secure provisioning, telemetry, and system health monitoring. Manage the Linux userspace configuration, covering device management, network management, process management, and time synchronization. Optimize system performance across CPU and GPU resources, leveraging CUDA for acceleration. Harden the platform for mixed-criticality real-time workloads using Preempt-RT, process isolation, and security best practices. Required Qualifications 8+ years of embedded Linux experience working with robotics, autonomous, or high-performance embedded systems. Expert knowledge of Linux systems programming, with a solid understanding of the kernel, device drivers, and hardware interfaces. Strong expertise with Linux services and userspace management, including systemd, udev, networkd, and shell scripting. Strong proficiency in C, C++, or Rust, with a willingness and excitement to work primarily in Rust. Track record of technical leadership: leading projects, driving design decisions, mentoring others, and working effectively across teams. Preferred Qualifications Experience with the NVIDIA Jetson ecosystem (Jetpack) Professional experience developing in Rust for embedded Linux environments. Background in robotics or autonomous vehicles, including experience optimizing sensor pipelines using CUDA. Knowledge of real-time Linux (PREEMPT_RT) and tuning mixed-criticality systems for deterministic performance. Experience building and maintaining custom Linux distributions using Yocto/OpenEmbedded.