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 /b to join their team. /p pIn this role you will join a company that leverages state-of-the-art Computer Vision and Machine Learning algorithms to scan high quality, relightable 3D models of objects and products at scale. /p pYou 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. /p h3Responsibilities as DataOps / MLOps Engineer /h3 ul liDesign and manage data storage systems for large datasets (multi-TB image data, 3D assets, training data). /li liBuild efficient data access patterns and movement strategies for distributed training and experimentation. /li liImplement dataset versioning and lineage tracking for reproducibility /li liSet up and maintain experiment tracking and model registry infrastructure (MLflow, Weights Biases). /li liBuild ML pipelines for data preprocessing, training, validation, and model registration (Kubeflow, Airflow, Prefect). /li liSupport distributed training workflows across multi-GPU clusters (PyTorch Distributed, Horovod, Ray). /li liProfile and optimize training pipelines: data loading bottlenecks, batch sizing, GPU memory utilization.



/li liEnsure reproducibility of experiments: environment pinning, data versioning, artifact management. /li liManage artifact storage and distribution (Docker registries, model registries, package repositories). /li liBuild tooling to improve developer productivity for ML workflows. /li /ul h3Requirements /h3 ul liExperience with data storage systems and large file handling (object storage, NFS, distributed filesystems). /li liKnowledge of dataset versioning tools (DVC, Delta Lake, or similar). /li liExperience with ML pipeline orchestration (Airflow, Prefect, Kubeflow). /li liFamiliarity with experiment tracking tools (MLflow, Weights Biases, Neptune). /li liUnderstanding of distributed training frameworks and patterns. /li liExperience with containerization (Docker) and CI/CD pipelines. /li liKnowledge of Python dependency and environment management. /li liExperience with model registries and deployment workflows. /li liFamiliarity with data quality validation frameworks. /li liKnowledge of 3D graphics processing or computer vision workflows. /li /ul pIf this role is of any interest please apply directly on LinkedIn or send a copy of your CV to /p pBy 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 Privacy Notice. /p /p #J-18808-Ljbffr

📌 DataOps / MLOps Engineer (Bressanone)
🏢 European Tech Recruit
📍 Bressanone