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 include training and fine-tuning models for Detection, Classification, and Segmentation (e.g., YOLO, ResNet, U-Net).
You will implement Multi-Object Tracking (MOT) algorithms for complex video streams.
The role requires writing production-grade Python code with a focus on modularity and scalability.
You will containerize applications using Docker for consistent deployment.

Requirements:

You must have 3+ years of experience in Computer Vision or Deep Learning.
Proficiency in Python, PyTorch, and OpenCV is required.
There is a strong preference for candidates with experience in NVIDIA TensorRT and model optimization techniques such as quantization and pruning.
A solid grasp of software engineering principles, including Git, testing, and CI/CD, is necessary.
You should be able to work on other non-vision AI implementations as needed.

The position offers the opportunity to work on cutting-edge AI technologies and contribute to high-performance model deployment.
You will gain experience in a collaborative environment focused on innovation and excellence in AI solutions.
The role provides a chance to enhance your skills in model optimization and software engineering practices.

Skills