Job Description: Computer Vision Engineer at EagleSight.ai
Overview
As a Computer Vision Engineer at EagleSight.ai, you will design, develop, and deploy cutting-edge vision algorithms that facilitate rapid scaling of our solutions for property-level applications. This role involves a combination of research, engineering, and deployment, transforming innovative ideas into robust, optimized models suitable for both edge and cloud platforms.
Location: Edmonton, Alberta In-office requirement: 3+ days/week
Note: Only local qualified candidates will be contacted.
Responsibilities
- Design & Implement: Develop computer vision solutions such as object detection, segmentation, and tracking for property deployments.
- Optimize & Accelerate: Use model compression, quantization, and hardware-specific optimizations (TensorRT, ONNX Runtime) for low latency and high throughput.
- Build End-to-End Pipelines: Create workflows for data ingestion, annotation, training, validation, and CI/CD, integrated with Project Intercept platform.
- Collaborate Cross-Functionally: Work with ML developers, software engineers, product managers, and designers to bring features from prototype to production.
- Deploy & Monitor: Containerize models with Docker and Kubernetes, implement automated deployment, and establish performance monitoring for continual improvement.
- Code Review & Mentorship: Uphold high engineering standards through peer reviews and mentorship.
- Stay on the Cutting Edge: Research emerging computer vision techniques and advise on their applicability.
Requirements
- 3+ years of experience in computer vision algorithms development.
- Strong foundations in CV with experience in OpenCV and frameworks like TensorFlow, PyTorch, or Caffe.
- Programming skills in Python; C++ is a plus.
- Knowledge of model optimization: quantization, pruning, hardware accelerators.
- Experience with real-time vision pipelines, especially for live video or embedded systems.
- Understanding of RESTful APIs, microservice architectures, CI/CD tools (GitHub Actions).
- Entrepreneurial mindset, adaptable to fast-paced environments.
Bonus Skills
- Familiarity with edge deployment SDKs (NVIDIA Jetson)
- Experience with GPU-accelerated frameworks (GStreamer, NVIDIA DeepStream)
- Infrastructure as code and container orchestration with tools like Ansible.
Job Highlights
Details about benefits, team, or other highlights can be inserted here.