Senior Computer Vision Engineer - Embedded Systems and CUDA

About the position

Any sufficiently advanced technology is indistinguishable from magic. We make cutting-edge solutions that feel as natural as breathing. Pushing the boundaries of what's possible, our team of industry veterans is raising the bar for autonomous and collaborative robots. We are developing and deploying, at scale, iconic people-centered robots. We know we have succeeded when customers ask why other robotic solutions don't feel like ours - effortless, intuitive, and delightful. We believe that all machines that have physical actuators will soon be intelligent. In a sense, all machines will become intelligent robots, and Robust.AI's software platform will power the intelligence of the world's machines. As our Senior Computer Vision Engineer - Embedded Systems and CUDA, you will be developing software that makes this vision a reality.

Responsibilities

• Collaborate with perception and robotics teams to develop and optimize code for NVIDIA Jetson platforms.
• Adapt and scale research solutions to run efficiently on robot hardware, maximizing the use of compute and sensors.
• Write clean, efficient, and well-tested code.
• Document APIs for seamless integration and understanding by other teams.

Requirements

• BS, MS, or PhD in Computer Science, Software Engineering, Electrical Engineering, or a related field.
• 2+ years of industry experience in software engineering.
• Proficiency in C++ and CUDA C.
• Expertise in optimizing software for NVIDIA Jetson platforms.
• Strong skills in software engineering and algorithm development.
• Familiarity with the Nvidia edge inference ecosystem (e.g. VPI, TensorRT, etc.).

Nice-to-haves

• Experience with multithreading and multithreading frameworks.
• Experience optimizing 2D and 3D vision algorithms for NVIDIA Jetson (e.g., stereo vision, optical flow, detection, tracking, pose estimation).
• Familiarity with deep learning algorithms and pipelines.
• Experience with sensor calibration (multi-camera systems, extrinsic/intrinsic calibration).
• Proficiency with embedded Linux (e.g., Yocto).
• Experience with specialized libraries, languages, and frameworks (e.g., PyTorch, TensorFlow, OpenCV, PCL).
• Familiarity with transport layers and inter-process communication for robotics systems (e.g., ROS, GRPC, Boost, Interprocess, NATS, ZeroMQ).
• Experience with shared memory for inter-process communication.