Edge Perception & ML Engineer – Real-Time Sensor Fusion

Open People Network (OPN); Toronto; On-site; CAD 120,000 - 170,000; Full time

Job summary

Osprey Systems seeks a skilled ML/edge AI engineer to fuse multi-sensor data into real-time, device-local inferences with sub-second latency. You will design a robust fusion engine, develop target classification under challenging conditions, and implement trajectory analysis on embedded GPUs.

You will work on field-collected data, labeling workflows, and model retraining, with a bias toward real-world validation. Collaboration across small teams and future hiring will shape the role.

Qualifications

• 4+ years building and shipping ML systems, including perception or tracking.
• Strong classical estimation alongside deep learning: filtering, data association, probabilistic reasoning.
• Edge or embedded deployment experience with real latency and memory constraints.
• Proficiency in Python and C++ for production-grade systems.
• Comfort with self-collected data and bias toward field validation over benchmarks.

Responsibilities

• Design and build the multi-sensor fusion engine that cross-validates detections into unified tracks with calibrated confidence.
• Develop classification models that separate targets from clutter and benign activity.
• Build behavioral inference: trajectory analysis, pattern recognition, and assessment.
• Deploy and optimize models for edge inference on embedded GPU hardware within strict latency budgets.
• Build field collection, labeling, dataset versioning, and retraining workflows.
• Handle low light, snow, fog, acoustic and RF noise as normal operating conditions.
• Help shape engineering culture, tooling, and hiring as the team grows.

Skills

ML systems

Edge computing

Field validation

Low-latency design

Python

C++

Tools

Python

C++

TensorRT

ONNX

CUDA

Job description

Osprey Systems seeks a skilled ML/edge AI engineer to fuse multi-sensor data into real-time, device-local inferences with sub-second latency. You will design a robust fusion engine, develop target classification under challenging conditions, and implement trajectory analysis on embedded GPUs.

You will work on field-collected data, labeling workflows, and model retraining, with a bias toward real-world validation. Collaboration across small teams and future hiring will shape the role.