Computer Vision Engineer

Description

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 computer vision/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).
• Ability to work on other non-vision AI implementations.