Senior Embedded Vision Engineer

• Design, train, and deploy computer vision models for real-time inference on edge devices, balancing accuracy, latency, and power constraints.
• Optimize models for embedded hardware (e.g., NVIDIA Jetson, Ambarella, ARM-based SoCs) using vendor SDKs to meet latency, memory, and power constraints.
• Identify and resolve performance bottlenecks across the full pipeline (data ingestion, preprocessing, inference, postprocessing) to meet strict real-time requirements.
• Work with camera data alongside onboard sensors such as IMUs and GPS, contributing to multi-sensor fusion approaches to improve system robustness and state estimation.

This role directly contributes to making shared micromobility safer and more sustainable by developing computer vision solutions that prevent unsafe riding behaviors and improve parking precision, reducing accidents and urban clutter.

• 5+ years of industry experience in Computer Vision and Machine Learning, with hands-on experience deploying models in real-world or embedded environments.
• Strong programming skills in C/C++ and Python, with experience developing and optimizing applications on resource-constrained devices.
• Experience with edge AI and embedded platforms (e.g., NVIDIA Jetson, Ambarella, ARM-based SoCs), including performance optimization under latency and power constraints.
• Familiarity with model deployment and optimization frameworks such as TensorRT, ONNX Runtime, OpenVINO, or similar.

Base salary range determined by location and experience; discretionary annual performance bonus opportunities and equity may be included. Remote work within Canada.

Lime is the largest global shared micromobility business, operating in close to 30 countries across five continents, on a mission to build a future where transportation is shared, affordable, and carbon-free.