Edge AI Systems Engineer – Robotics Integration

Job Title:

Edge AI Systems Engineer – Robotics Integration

Location:

Vancouver, CA (Hybrid or On-site)

About the Role:

Our client, an innovator at the forefront of robotics and AI, is seeking an Edge AI Systems Engineer to accelerate machine learning deployment across real-time, embedded robotics systems. In this hands-on role, you’ll be instrumental in optimizing model performance on edge devices—making AI truly mobile and responsive. You’ll help bring advanced perception and decision-making capabilities directly to the edge, where robots interact with the world in real time.

This is a rare opportunity to join a high-growth team developing the next generation of robotic intelligence. With strong cross-functional collaboration and access to cutting-edge hardware, you’ll play a key role in shaping products that are redefining autonomy.

Key Responsibilities:

• Optimize and deploy machine learning models for real-time inference on resource-constrained edge platforms

• Convert, quantize, and compress AI models using frameworks like Tensor

RT, ONNX, or TFLite

• Integrate AI components with real-time sensor inputs, perception pipelines, and robotic control systems

• Build and maintain low-latency pipelines for mission-critical AI workloads including object detection, tracking, and localization

• Partner with cross-disciplinary teams (robotics, hardware, AI/ML) to ensure cohesive product integration

• Benchmark and profile model and system performance across different edge compute environments

• Contribute to end-to-end deployment strategies, from simulation to physical testing

Qualifications:

• Bachelor’s or Master’s degree in Electrical Engineering, Robotics, Computer Engineering, or related technical field

• 2+ years of experience developing for embedded platforms with AI or ML workloads

• Proficient in C++ and Python, with experience in ML frameworks such as PyTorch or Tensor Flow

• Hands-on with edge computing devices like NVIDIA Jetson (Nano, Xavier), Qualcomm Snapdragon, or ARM Cortex architectures

• Skilled in embedded AI tools like Tensor

RT, OpenVINO, ONNX, or TFLite

• Deep understanding of real-time constraints, compute limitations, and memory optimization

Preferred Experience:

• Familiarity with ROS/ROS2 and integrating AI into robotic software ecosystems

• Background in embedded Linux, RTOS, or bare-metal programming environments

• Experience working with vision-based AI (segmentation, detection, classification)

• Familiarity with Docker, Yocto, or similar deployment pipelines for embedded development

What’s in It for You:

• Competitive compensation package with hybrid flexibility based out of Burnaby, BC

• Direct impact on advanced robotics products at the intersection of AI and embedded systems

• Daily collaboration with expert teams in a hands-on, engineering-driven environment

• Exposure to real-world robotics challenges with access to state-of-the-art edge AI infrastructure

• Autonomy, ownership, and technical mentorship in a mission-driven team environment

Take your embedded AI skills to the edge—where the future of robotics is being built.