EAIGLE is a computer vision AI platform helping enterprises in supply chain and logistics turn vision data into security, transportation, and operational outcomes. Our solutions include AVAC™ , automated vehicle access control at the retailer's gate, and YardSight™ , real-time monitoring of loading docks and truck parking availability across the yard. The platform combines on-premise computer vision components with Azure cloud services, and is deployed today at Fortune 100 and 500 companies.

The Role

We're looking for a Computer Vision Researcher to take AI solutions for image and video understanding from research through to production. You'll own problems end to end: framing them, experimenting, building and training models, evaluating rigorously, optimizing for real-world constraints, and shipping to cloud and edge environments.

This is a role for someone who is comfortable moving between a paper and a production incident in the same week, and who is willing to pick up whatever technology the problem requires.

What You'll Do

- Research, adapt, and deploy state-of-the-art computer vision and deep learning methods for our products.
- Design, train, fine-tune, and evaluate models across detection, tracking, segmentation, OCR, and related vision tasks.
- Build the data pipelines behind the models — collection, annotation, augmentation, and preprocessing at scale.
- Optimize models for accuracy, latency, memory, and cost, and deploy them to cloud and edge environments.
- Define evaluation metrics, benchmark rigorously, and monitor deployed models to drive the next iteration.




- Document your findings and designs clearly, and contribute to publications, patents, or open source where it makes sense.

What We're Looking For

- Master's or PhD in Computer Science, AI, Electrical Engineering, Mathematics, or a related technical field.
- Substantial research or professional experience in computer vision and deep learning.
- Depth in 3D camera geometry and motion. This is central to what we do, and we want someone who has genuinely worked in this space — 3D tracking, structure from motion, visual SLAM, multi-view geometry, camera calibration and pose estimation, stereo or depth estimation, or closely adjacent problems.
- Strong Python skills, with hands-on experience in PyTorch and/or TensorFlow and OpenCV.
- Experience taking models from experiment to production.
- Comfort working across Linux and Windows, with Git and modern engineering practices.
- Strong analytical and communication skills, and the self-direction to work through ambiguous problems.

Nice to Have

- Experience with up-to-date architectures and frameworks such as Vision Transformers, YOLO, SAM, CLIP, diffusion models, or vision-language and multimodal systems.
- Inference optimization and acceleration experience — quantization, pruning, distillation, ONNX, TensorRT, OpenVINO, CUDA.
- Edge AI or embedded deployment experience.
- Familiarity with Azure or another major cloud platform, and with MLOps tooling and ML pipelines.
- Experience with containerized deployment with Docker
- C++ alongside Python.
- Publications at recognized vision or AI venues, or contributions to open-source vision projects.

📌 Computer Vision Researcher / Developer (Markham)
🏢 EAIGLE
📍 Markham