Computer Vision Engineer (EalgeSight.ai)

Key Skills

Ansible, API, C++, Caffe, Computer Vision (CV), Continuous Integration & Continuous Delivery - CI/CD, Github, Infrastructure as code, NVIDIA Jetson, OpenCV, Optimization, Python Programming, PyTorch, RESTful, SDK, TensorFlow

Job Description

What You'll Do:

• Design & Implement – Develop and productionize computer vision solutions (e.g. object detection, segmentation, tracking) tailored for property‑level deployments
• Optimize & Accelerate – Apply model compression, quantization, and hardware‑specific optimizations (TensorRT, ONNX Runtime, etc.) to achieve low latency and high throughput on edge devices and on-prem servers.
• Build End‑to‑End Pipelines – Create data ingestion, annotation, training, validation, and CI/CD workflows that seamlessly integrate with our Project Intercept platform
• Collaborate Cross‑Functionally – Partner with ML Developers, Software Engineers (frontend & backend), Product Managers, and Designers to bring features from prototype to production
• Deploy & Monitor – Containerize models (Docker, Kubernetes) for automated deployment, then instrument performance monitoring and feedback loops to continually improve accuracy and reliability
• Code Review & Mentorship – Maintain high engineering standards through peer reviews and knowledge sharing, supporting the growth of our vision‑AI practice
• Stay on the Cutting Edge – Research emerging computer vision techniques and recommend the best fit for our product roadmap

What You Bring:

• 3+ years of experience developing computer vision algorithms Strong CV Foundations – Hands‑on experience with OpenCV and deep learning frameworks such as TensorFlow, PyTorch, or Caffe
• Programming Expertise – Proficient in Python; C++ experience an asset for performance‑critical components
• Model Optimization Skills – Familiarity with quantization, pruning, and hardware accelerators (GPU, VPU)
• Real‑Time Processing Know‑How – Experience building vision pipelines for live video streams or embedded systems
• API & Microservices – Solid understanding of RESTful APIs, microservice architectures, and CI/CD tooling (e.g., GitHub Actions)
• Entrepreneurial Mindset – Thrive in a fast‑paced environment, ready to iterate quickly and own end‑to‑end delivery

Bonus Points:

• Familiarity with edge‑deployment SDKs (e.g., NVIDIA Jetson)
• Experience with GPU accelerated frame capture/processing pipelines such as GStreamer/NVIDIA DeepStream SDK
• Background in container orchestration or infrastructure as code using Ansible