Hybrid ML Engineer — YOLO & Computer Vision Pro

Ultralytics; Madrid; Hybrid; EUR 69,000 - 114,000; Full time

Benefits offered by this job

Hybrid flexibility

24 days vacation

Birthday off

Apple gear

Job summary

Ultralytics in Shenzhen, China, is seeking a seasoned Machine Learning Engineer to drive end-to-end development of Ultralytics YOLO models. You will design, train, and deploy state-of-the-art computer vision solutions, leveraging Python and PyTorch, CUDA, and modern MLOps practices.

You will build scalable pipelines, optimize models for diverse hardware using TensorRT, OpenVINO and ONNX Runtime, manage large datasets, contribute to open-source repositories, and document learnings for the

Qualifications

• 5+ years of professional experience in Machine Learning Engineering.
• Deep expertise in Python and PyTorch.
• Proven experience with computer vision and an understanding of transformer and CNN architectures.
• Hands-on experience with model optimization (quantization and pruning) and deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO.

Responsibilities

• Developing, training, and validating state-of-the-art models for computer vision tasks including detection, segmentation, and classification.
• Writing efficient, scalable production-grade Python code using PyTorch.
• Optimizing models for high-performance inference on diverse hardware using TensorRT, OpenVINO, and ONNX Runtime.
• Managing and processing large-scale datasets and implementing advanced data augmentation strategies.
• Designing and maintaining robust CI/CD pipelines with GitHub Actions for automated training, testing, and benchmarking.
• Collaborating with research and engineering teams to implement cutting-edge techniques and contribute to open-source repositories.
• Engaging with the community by creating documentation and tutorials to help users solve real-world problems.

Skills

Python

PyTorch

Computer Vision

Data augmentation

CUDA

MLOps

GitHub Actions

Docker

TensorRT

ONNX Runtime

OpenVINO

Open-source contributions

Tools

GitHub Actions

Docker

NVIDIA TensorRT

OpenVINO

ONNX Runtime

PyTorch

Job description

Ultralytics in Shenzhen, China, is seeking a seasoned Machine Learning Engineer to drive end-to-end development of Ultralytics YOLO models. You will design, train, and deploy state-of-the-art computer vision solutions, leveraging Python and PyTorch, CUDA, and modern MLOps practices.

You will build scalable pipelines, optimize models for diverse hardware using TensorRT, OpenVINO and ONNX Runtime, manage large datasets, contribute to open-source repositories, and document learnings for the