Edge AI Systems Engineer – Robotics Integration

Blue Signal; Vancouver; Hybrid; CAD 90,000 - 130,000; Full time

Job summary

A leading company in robotics and AI is seeking an Edge AI Systems Engineer to optimize machine learning deployment on real-time embedded systems. This role involves hands-on work with innovative technologies, contributing to cutting-edge robotics products that redefine autonomy, including optimization of AI models and integration with robotic systems, within a collaborative, high-growth environment.

Benefits

Competitive compensation package

Direct impact on advanced robotics products

Daily collaboration with expert teams

Exposure to real-world robotics challenges

Autonomy and technical mentorship

Qualifications

• 2+ years of experience developing for embedded platforms with AI or ML workloads.
• Hands-on with edge computing devices like NVIDIA Jetson, Qualcomm Snapdragon.
• Skilled in embedded AI tools and deep understanding of real-time constraints.

Responsibilities

• Optimize and deploy machine learning models for real-time inference on edge platforms.
• Integrate AI components with real-time sensor inputs and robotic control systems.
• Contribute to end-to-end deployment strategies from simulation to testing.

Skills

C++

Python

Machine Learning

Embedded Systems

Education

Bachelor’s or Master’s degree in Electrical Engineering

Degree in Robotics or Computer Engineering

Tools

TensorRT

ONNX

TFLite

PyTorch

TensorFlow

Job description

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.

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