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)