Perception / ML Engineer

Job summary

Build an on-device multi-sensor fusion engine that combines detections into unified tracks with calibrated confidence, and develop classification and behavioral inference models to distinguish targets from benign activity and environmental clutter. Optimize models for embedded GPU hardware, establish data collection and retraining workflows, and validate performance in challenging field conditions.

Job details

Osprey Systems is building Canada’s sovereign counter-drone capability. Our distributed detection and interception system is designed for the environments where everything else fails: extreme cold, GPS-denied, and network-degraded conditions. We serve critical infrastructure operators and defense customers with a single product line, built in Canada. We are a small founding team backed by a clear funding pathway through Canadian defense innovation programs and paid civilian deployments. The role Our systems sense the world through several independent modalities at once. Your job is fusing them into one trustworthy answer, computed on the device itself, in well under a second, without cloud, satellite navigation, or a reliable network. False positives are what kill sensing products. Your work is the cure. What you will do Design and build the multi-sensor fusion engine that cross-validates independent detections into unified tracks with calibrated confidence. Develop classification models that separate targets of interest from benign activity and environmental clutter. Build behavioral inference on top of classification: trajectory analysis, pattern recognition, and assessment. Deploy and optimize models for edge inference on embedded GPU hardware under strict latency budgets. Build field collection, labeling, dataset versioning, and retraining workflows. Handle low light, snow, fog, acoustic noise, and RF noise as normal operating conditions. Help shape engineering culture, tooling, and hiring as the team grows. What we are looking for 4+ years building and shipping ML systems, including perception, tracking, or multi-sensor problems. Strong classical estimation alongside deep learning: filtering, data association, probabilistic reasoning. Edge or embedded deployment experience with real latency and memory constraints. Python and C++ proficiency. Comfort with small, messy, self-collected datasets. Bias toward field validation over benchmark metrics. Nice to have: Classification in cluttered or adversarial sensor environments; multi-object tracking; robotics or autonomous-systems perception; TensorRT, ONNX or CUDA depth; early-stage startup experience. Apply Now First Name* Last Name* Email Address* Country* Linkedin* Position* Salary Expectation* Upload Resume* Join Our Community We’ll send you job opportunities, Q&As with industry leaders, career insights, and more.

What you’ll do

Build an on-device multi-sensor fusion engine that combines detections into unified tracks with calibrated confidence, and develop classification and behavioral inference models to distinguish targets from benign activity and environmental clutter. Optimize models for embedded GPU hardware, establish data collection and retraining workflows, and validate performance in challenging field conditions.

Requirements

Requires 4+ years of experience building and shipping machine-learning systems, including perception, tracking, or multi-sensor applications, with strong classical estimation and deep-learning skills. Candidates should have edge or embedded deployment experience, proficiency in Python and C++, and comfort working with small, messy, self-collected datasets.

Listed skills

• Machine learning · Preferred
• C++ · Preferred
• Tracking · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Multi-Sensor Fusion
• Machine Learning
• Perception
• Classification
• Tracking
• Probabilistic Reasoning
• Filtering
• Data Association
• Edge Inference
• Embedded GPU Deployment
• Python
• C++
• Dataset Versioning
• Model Optimization
• Trajectory Analysis
• Field Validation

Job areas

• Engineering
• Software
• Technology
• Security & Safety
• Data & Analytics