ALLSIDES is redefining how the world experiences 3D content. We combine physically accurate scanning and generative AI to power content creation workflows for e-commerce, virtual environments, and immersive experiences. Our clients include global brands like adidas, Meta, Amazon, and Zalando.We operate a rapidly scaling photorealistic 3D scanning operation, capturing tens of thousands of assets annually while training next-generation AI models. As an NVIDIA Inception member, we collaborate with leading research institutions and actively participate in top-tier conferences in 3D computer vision and AI.More info: https://www.allsides.tech | https://blogs.nvidia.com/blog/covision-adidas-rtx-ai/Position OverviewWe'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.Main ResponsibilitiesDesign 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 experimentationImplement dataset versioning and lineage tracking for reproducibilitySet 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 utilizationEnsure reproducibility of experiments: environment pinning, data versioning, artifact managementManage artifact storage and distribution (Docker registries, model registries, package repositories)Build tooling to improve developer productivity for ML workflowsQualificationsStrong Linux knowledgeExperience 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 patternsExperience with containerization (Docker) and CI/CD pipelinesKnowledge of Python dependency and environment managementNice to HaveExperience with model registries and deployment workflowsFamiliarity with data quality validation frameworksKnowledge of 3D graphics processing or computer vision workflowsWhat we offerCompensation that reflects your experience including stock-optionsLunch voucher for working daysWe assist with relocationFlexible working hours and work-from-home policyFamily-friendly environmentAmazing office space in South Tyrol, located at the Durst GroupPersonal and professional growth opportunitiesYou don't have to tick every box to apply, your drive and passion matter most!This role is located on-site in Brixen/Bressanone, Italy. If you are interested, please apply with your CV attached to careers@allsides.tech
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