Physical AI, Computer Vision Engineer - Remote

Originally posted 17 June 2026 by the employer.

About the role

Develop software for intelligent edge systems that combine embedded computing, real-time processing, computer vision, and AI. The role spans embedded Linux and RTOS platforms across heterogeneous computing architectures including CPUs, GPUs, FPGAs, and dedicated AI accelerators.

What you'll do

- Design, develop, and maintain embedded software for AI-enabled edge computing platforms. - Develop software for Linux and Real-Time Operating Systems (RTOS) supporting deterministic, low-latency execution. - Design and implement real-time software for perception, sensor processing, control, and autonomous decision-making. - Develop and integrate computer vision, image processing, and AI inference applications for real-world deployment. - Optimize software and pipelines across heterogeneous computing architectures including CPUs, GPUs, FPGAs, and AI accelerators. - Support platform bring-up, debugging, validation, and system integration while analyzing latency, throughput, memory utilization, and power efficiency.

What you'll need

- Experience developing software for embedded Linux and Real-Time Operating Systems (RTOS). - Experience with real-time processing, perception, sensor processing, and system optimization. - Experience developing and integrating computer vision, image processing, and AI inference applications. - Experience with software optimization across heterogeneous computing architectures including CPUs, GPUs, FPGAs, or AI accelerators. - Experience with platform bring-up, debugging, validation, and system integration.

Nice to have

- Experience with RTOS platforms such as QNX, GreenHills, or similar real-time operating systems. - Experience designing software for low-latency, safety-critical, or time-sensitive embedded applications. - Experience with AMD Vitis™ AI or equivalent AI deployment frameworks. - Experience with AMD Ryzen™ Embedded, EPYC™ Embedded, Versal™ AI Edge, Zynq UltraScale+, Kria™, or similar edge computing platforms. - Understanding of FPGA-based acceleration and hardware/software co-design methodologies. - Experience with AI inference deployment using ONNX, PyTorch, TensorFlow, or related frameworks. - Experience with ROS 2 and robotics software architectures. - Understanding of perception systems including cameras, radar, lidar, and sensor fusion technologies. - Familiarity with graphics and visualization technologies such as OpenGL, Vulkan, or Wayland. - Experience with Linux kernel, BSP, device driver, or low-level platform software development. - Experience within robotics, automotive, industrial automation, aerospace, machine vision, or related embedded systems domains.

Skills: embedded software, computer vision, real-time processing, RTOS, edge AI