Role overview

Geotab is a global leader in IoT and connected transportation, processing billions of data points daily to help businesses manage their fleets, enhance driver safety, and optimize operations. The company seeks a Senior Computer Vision Engineer to deliver advanced, high-precision Edge AI technical contributions for Geotab’s camera systems, working in Oakville, Ontario.

Key responsibilities

Design, implement, and validate novel deep learning architectures including CNNs and Transformers for real-time edge processing, covering object detection, segmentation, tracking, scene understanding, and sensor fusion applications.
Optimize models intensely for accuracy and ultra-low-latency performance on edge devices, applying advanced quantization, pruning, and knowledge distillation techniques to ensure reliable deployment with hardware accelerators.
Continuously improve codebase structure, model training frameworks, and deployment pipelines to enhance testability, robustness, and maintainability.
Build, automate, and refine edge model monitoring tools and continuous integration/deployment pipelines to guarantee sustained reliability and seamless field updates.
Diagnose and troubleshoot complex model training failures, inference bottlenecks, and live field performance issues by investigating systemic failure modes.
Independently write, co-write, and critically review technical design documentation for complex camera systems and feature sets.
Mentor less senior engineers and interns on an individual basis, actively participating in Geotab’s engineering interview and recruiting process.
Partner with adjacent engineering teams, camera software engineers, and platform developers to clear roadblocks and execute major feature releases.

Requirements

Advanced hands-on proficiency in computer vision, machine learning, and edge deployment ecosystems.
Demonstrated ability to design and optimize deep learning models for ultra-low-latency performance on edge hardware.
Strong analytical skills and experience troubleshooting complex failure modes in production systems.
Pragmatic project ownership capabilities with the ability to tackle systemic challenges under tight time constraints.
Experience with continuous integration/deployment pipelines and model monitoring in production environments.
Ability to mentor junior engineers and contribute meaningfully to technical hiring processes.

What makes this role worth considering

Geotab is a certified Great Place to Work with a fast-paced, inclusive culture that encourages innovation and professional growth. The role offers opportunities to work on cutting-edge Edge AI systems that directly impact fleet management, driver safety, and sustainability across a global customer base.