Computer Vision Engineer (PyTorch/TensorRT)

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