Senior Embedded Vision Engineer — Real-Time Edge AI

vividmachines; Toronto; On-site; CAD 120,000 - 170,000; Full time

Benefits offered by this job

Competitive compensation

Competitive benefits package

Open, friendly, collaborative culture

Team events and retreats

Free drinks and snacks

Job summary

Vivid Machines seeks a Senior Engineer to design and implement real-time vision systems spanning embedded hardware, cloud, and mobile layers. You will work on multi-camera capture, on-device inference, and geolocation, driving reliability in harsh field environments.

You will join a small, high-impact team focused on solving hard problems in farming technology and agriculture robotics at scale, with a strong emphasis on performance, observability, and end-to-end quality.

Qualifications

• Strong systems programming ability in a compiled language (C, C++, or Rust).
• Experience building real-time streaming media or vision pipelines.
• Hands-on experience deploying vision models to edge devices.
• Experience with cameras and sensors at a low level (image sensors, capture drivers, I2C/SPI/GPIO).
• Comfort with Linux as an embedded platform: kernel customization and debugging, containers, cross-compilation.
• Experience making distributed or embedded systems observable (metrics/logs/dashboards).
• Self-direction in a small, distributed team.

Responsibilities

• Own the capture and inference pipeline across multi-camera video and model storage, with no dropped frames.
• Make heavy vision models run in real time on fixed hardware with bounded power/thermal budgets.
• Bring up cameras and sensors at the driver level.
• Turn sensor data into per-tree geolocation by fusing vision, position, and motion data.
• Support reproducible field problems with on-device CI and ground-truth regression testing.
• Ensure observability of devices via metrics/logs and alerting for issues.

Job description

Vivid Machines seeks a Senior Engineer to design and implement real-time vision systems spanning embedded hardware, cloud, and mobile layers. You will work on multi-camera capture, on-device inference, and geolocation, driving reliability in harsh field environments.

You will join a small, high-impact team focused on solving hard problems in farming technology and agriculture robotics at scale, with a strong emphasis on performance, observability, and end-to-end quality.