Dataops & Mlops Engineer (F/M/D)

Position Overview

We're looking for a DataOps & MLOps Engineer to build the infrastructure that powers our data and ML workflows. You'll focus on data storage and movement, dataset versioning, ML pipeline automation, experiment tracking, and ensuring reproducibility across our 3D reconstruction and training workloads.

This full-time role is located on-site at our office in Brixen/Bressanone, Italy.

Main Responsibilities

• Design and manage data storage systems for large datasets (multi-TB image data, 3D assets, training data)
• Build efficient data access patterns and movement strategies for distributed training and experimentation
• Implement dataset versioning and lineage tracking for reproducibility
• Set up and maintain experiment tracking and model registry infrastructure (MLflow, Weights & Biases)
• Build ML pipelines for data preprocessing, training, validation, and model registration (Kubeflow, Airflow, Prefect)
• Support distributed training workflows across multi-GPU clusters (PyTorch Distributed, Horovod, Ray)
• Profile and optimize training pipelines: data loading bottlenecks, batch sizing, GPU memory utilization
• Ensure reproducibility of experiments: environment pinning, data versioning, artifact management
• Manage artifact storage and distribution (Docker registries, model registries, package repositories)
• Build tooling to improve developer productivity for ML workflows

Qualifications Required

• Strong Linux knowledge
• Experience with data storage systems and large file handling (object storage, NFS, distributed filesystems)
• Knowledge of dataset versioning tools (DVC, Delta Lake, or similar)
• Experience with ML pipeline orchestration (Airflow, Prefect, Kubeflow)
• Familiarity with experiment tracking tools (MLflow, Weights & Biases, Neptune)
• Understanding of distributed training frameworks and patterns
• Experience with containerization (Docker) and CI/CD pipelines
• Knowledge of Python dependency and environment management
• English skills, German or Italian is an advantage

Nice to Have

• Experience with model registries and deployment workflows
• Familiarity with data quality validation frameworks
• Knowledge of 3D graphics processing or computer vision workflows

Benefits

• Competitive salary package
• Stock Options
• Flexible working hours, Remote work
• Lunch voucher for working days
• Small team, flat hierarchy
• Personal and professional growth opportunities: Take over and own important parts of infrastructure development and help us blitz-scale
• Relocation assistance
• Visa sponsorship
• Access to a coffee-bar and gym at Durst AG

You don’t have to tick every box to apply, your drive and passion matter most! If you’re curious, motivated, and ready to learn, send us your application.