Computer Vision Engineer (PyTorch/TensorRT)

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