PpEuropean Tech Recruit are working closely with a market leading 3D scanning company, based in Bressanone, who are looking for a talented bDataOps / MLOps Engineer /bto join their team. /ppIn this role you will join a company that leverage state-of-the-art Computer Vision and Machine Learning algorithms to scan high quality, relightable 3D models of objects and products at scale. /ppYou will help to build the infrastructure that powers their data and ML workflows. You'll focus on data storage and movement, dataset versioning, ML pipeline automation, experiment tracking, and ensuring reproducibility across the 3D reconstruction and training workloads. /ph3Responsibilities as DataOps / MLOps Engineer: /h3ulliDesign and manage data storage systems for large datasets (multi-TB image data, 3D assets, training data). /liliBuild efficient data access patterns and movement strategies for distributed training and experimentation. /liliImplement dataset versioning and lineage tracking for reproducibility /liliSet up and maintain experiment tracking and model registry infrastructure (MLflow, Weights Biases). /liliBuild ML pipelines for data preprocessing, training, validation, and model registration (Kubeflow, Airflow, Prefect). /liliSupport distributed training workflows across multi-GPU clusters (PyTorch Distributed, Horovod, Ray). /liliProfile and optimize training pipelines: data loading bottlenecks, batch sizing, GPU memory utilization. /liliEnsure reproducibility of experiments: environment pinning, data versioning, artifact management. /liliManage artifact storage and distribution (Docker registries, model registries, package repositories). /liliBuild tooling to improve developer productivity for ML workflows. /li /ulh3Requirements: /h3ulliExperience with data storage systems and large file handling (object storage, NFS, distributed filesystems). /liliKnowledge of dataset versioning tools (DVC, Delta Lake, or similar). /liliExperience with ML pipeline orchestration (Airflow, Prefect, Kubeflow). /liliFamiliarity with experiment tracking tools (MLflow, Weights Biases, Neptune). /liliUnderstanding of distributed training frameworks and patterns. /liliExperience with containerization (Docker) and CI/CD pipelines. /liliKnowledge of Python dependency and environment management. /liliExperience with model registries and deployment workflows. /liliFamiliarity with data quality validation frameworks. /liliKnowledge of 3D graphics processing or computer vision workflows. /li /ulpIf this role is of any interest please apply directly on LinkedIn or send a copy of your CV to /ppBy applying to this role you understand that we may collect your personal data and store and process it on our systems. For more information please see our a Privacy Notice /a. /p /p #J-18808-Ljbffr