Computer Vision Engineer (PyTorch/TensorRT)
EgyptRemote
AI Summary
Three-plus years of computer vision experience focusing on training, optimizing, and deploying deep learning models (detection, segmentation, MOT) using PyTorch, TensorRT, and Docker in production-ready Python code.
About this role
We are seeking a Computer Vision Engineer with strong software and AI fundamentals to build and deploy high-performance AI models. You will handle the full pipeline—from training detection and segmentation models to optimizing them for production using NVIDIA TensorRT and Docker.
Core Responsibilities
- Model Training: Train and fine-tune models for Detection, Classification, and Segmentation (e.g., YOLO, ResNet, U-Net).
- Tracking: Implement Multi-Object Tracking (MOT) algorithms for complex video streams.
- Engineering: Write production-grade Python code with a focus on modularity and scalability.
- Deployment: Containerize applications using Docker for consistent deployment.
Requirements
- 3+ years in CV/Deep Learning.
- Python, PyTorch, OpenCV.
- Strong preference for experience with NVIDIA TensorRT and model optimization (quantization/pruning).
- Solid grasp of software engineering principles (Git, testing, CI/CD).
- Can work on other non-vision AI implementations
Skills
CI/CDDockerGitModel PruningModel QuantizationMult-Object Tracking (MOT)OpenCVPythonPyTorchResNetTensorRTTestingU-NetYOLO
