ML Engineer

A fast-growing tech company and global leader in digital image processing is looking for its next Machine Learning Engineer with strong computer vision experience. You’ll build and deploy production-ready ML models for photo and video enhancement across desktop, mobile, and cloud platforms. Ideal for someone who loves turning research into real-world, high-impact solutions.

Responsibilities

• Work with R&D team lead to research how best to develop various image corrections to bolt onto our existing tech stack.
• Develop cutting edge custom ML solutions for automatic image and video processing.
• Design and run experiments: data preparation, model selection, training, evaluation.
• Collaborate with Image Quality specialists to refine unique in-house datasets.
• Optimize and convert models to inference-ready formats (CPU/GPU/NPU).
• Work with MLOps to deploy models into SDKs and production environments.

Requirements

• 3+ years of ML engineering experience in Computer Vision.
• Strong Python skills, experience with OpenCV, PIL, scikit-image.
• Hands-on expertise with PyTorch (primary) and TensorFlow 2.
• Experience with Generative Models (GANs, Diffusion, ViTs) and Image Restoration/Enhancement (denoising, deblurring, retouching).
• Experience in Image Segmentation, Face/Skin Detection, and Quality Improvement.
• Skilled with large datasets, training pipelines, Git, Docker, Bash, and Jira/Confluence.
• Proven track record of production-level model deployment; experience with video ML tasks is a plus.
• Good command of English.

Bonus skills

• Model deployment and optimization with CoreML, TensorFlow Lite, ONNX Runtime, Metal, OpenCL/OpenGL.
• Experience optimizing models for mobile devices and NPUs.
• Production-grade SDK integration.

Job conditions

• Full-time.
• A position with a multi-platform, global development team.
• Open to applicants based around the world, but focused on Eastern EU.
• Contract.

Support a global team: most developers are in the Eastern or Central EU, but many customers are in North America. Work hours are flexible, but be ready for work covering both EU and US standard work hours.