Lead Machine Learning Engineer (3D Data)

TL;DR

Lead Machine Learning Engineer (3D Data): Design and deploy machine learning and deep learning models for 3D point clouds and 3D reconstructions with an accent on 3D data pipelines, point-based architectures, and productionizing research methods. Focus on building scalable training pipelines, integrating 3D ML into existing workflows, and improving model quality using geometric and perceptual metrics.

Company

hirify.global builds spatial intelligence technology for reality capture and digital factory solutions.

What you will do

• Design and optimize ML/DL models for 3D point cloud tasks including filtering, denoising, registration, and surface reconstruction.
• Own 3D data pipelines end-to-end: preprocessing, augmentation, model adaptation, and evaluation against ground-truth geometry.
• Integrate 3D ML solutions into existing workflows and products in collaboration with cross-functional teams.
• Adapt state-of-the-art 3D deep learning methods for production use (e.g., PointNet++, sparse voxel/convolutional networks, graph neural networks, implicit/neural representations).
• Build scalable, reproducible training pipelines for large 3D datasets and improve performance using geometric/perceptual quality metrics.

Requirements

• MS or PhD in computer vision, machine learning, computer science, or a related field, or equivalent practical experience.
• 5–7+ years of hands-on experience applying ML/DL to point cloud processing, filtering, registration, or surface reconstruction, with strong theoretical grounding.
• Experience with point cloud-specific deep learning architectures (e.g., PointNet++, sparse convolutional networks, graph neural networks, transformer- or diffusion-based 3D models).
• Strong Python skills and hands-on experience with PyTorch, TensorFlow, and/or scikit-learn.
• Solid foundation in geometry, linear algebra, and optimization.
• Fluent English communication skills for collaboration with AI researchers, software engineers, and product designers.

Culture & Benefits

• Hybrid work setup with flexible working hours.
• 30 days of paid time off per year.
• Wellness and fitness support via EGYM Wellpass subsidy.
• Deutschlandticket subsidy and JobRad bike leasing model.
• Full visa and relocation support for international candidates.
• Competitive compensation package and up to 4000 EUR employee referral bonus; support for local language classes.

Hiring process

• Screening call followed by up to 4 interview rounds.
• Interviews include discussions to understand role fit and how the collaboration can support mutual growth.

Location: Munich (Hybrid, hirify.global GmbH)