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 TensorRT, 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 TensorFlow
• Hands-on with edge computing devices like NVIDIA Jetson (Nano, Xavier), Qualcomm Snapdragon, or ARM Cortex architectures
• Skilled in embedded AI tools like TensorRT, 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.
Edge AI Systems Engineer – Robotics Integration • Vancouver, CA
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