Senior ML Engineer — Computer Vision & YOLO (Hybrid)

Ultralytics; Madrid; Hybrid; EUR 80,000 - 120,000; Full time

Benefits offered by this job

Equity packages

Hybrid flexibility

24 days vacation

Birthday off

Apple gear

Team environment

Job summary

Ultralytics is looking for an experienced Machine Learning Engineer to join our Shenzhen team in a hybrid setup (3 days in-office, 2 remote). You will develop and refine our YOLO models from research to deployment and collaborate with researchers and engineers.

You will work with Python/PyTorch, optimize across GPUs, contribute to open-source, and create documentation and tutorials for users of Ultralytics technology. Applicants must be eligible to work in China.

Qualifications

• 5+ years of professional experience in Machine Learning Engineering or a similar role.
• Deep expertise in Python and deep learning frameworks, with a strong preference for PyTorch.
• Proven experience with computer vision and a strong understanding of model architectures like transformers and CNNs.
• Hands-on experience with model optimization (i.e., quantization and pruning) and model deployment frameworks such as TensorRT, ONNX Runtime, and OpenVINO.
• Proficiency with CUDA programming and optimizing code for GPU acceleration.
• Strong background in MLOps practices, including CI/CD using GitHub Actions and containerization with Docker.
• Excellent problem-solving skills and the ability to thrive in a fast-paced, high-intensity environment.
• Experience contributing to major open-source projects is a significant advantage.

Responsibilities

• Developing, training, and validating state-of-the-art models for computer vision tasks.
• Writing efficient, scalable Python code using PyTorch.
• Optimizing models for high-performance inference across hardware using TensorRT, OpenVINO, and ONNX.
• Managing and processing large-scale datasets and implementing data augmentation strategies.
• Designing and maintaining 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 for users of Ultralytics technology.

Skills

Python

PyTorch

Computer vision

CUDA

MLOps

GitHub Actions

Docker

TensorRT

ONNX Runtime

OpenVINO

Open-source

Tools

CUDA toolkit

NVIDIA TensorRT

OpenVINO toolkit

ONNX Runtime

Docker

Job description

Ultralytics is looking for an experienced Machine Learning Engineer to join our Shenzhen team in a hybrid setup (3 days in-office, 2 remote). You will develop and refine our YOLO models from research to deployment and collaborate with researchers and engineers.

You will work with Python/PyTorch, optimize across GPUs, contribute to open-source, and create documentation and tutorials for users of Ultralytics technology. Applicants must be eligible to work in China.