Let us shape the future together!
Your Role & Responsibilities
Design, build, and maintain scalable data pipelines that support the full data lifecycle—from collection and annotation to quality assurance, governance, and cloud storage.
Develop and optimize infrastructure that enables high-quality datasets to flow efficiently into machine learning training pipelines.
Contribute to the design and evolution of a cloud-based data platform, including ingestion pipelines, labeling workflows, dataset cataloging, versioning, and compliance.
Implement processes and tooling that improve data quality, reliability, and observability across the data lifecycle.
Work closely with research and engineering teams to support the creation and management of large-scale datasets for advanced machine learning models.
Support data collection and integration workflows from robotics and sensor-based systems, including environments built on ROS2 or similar frameworks.
Contribute to best practices for data engineering, documentation, testing, and reproducible data pipelines.
Required Technical & Professional Expertise
5+ years of professional experience in data engineering, machine learning infrastructure, or related fields.
Strong experience designing and building large-scale data pipelines and distributed data processing systems.
Solid experience working with cloud-based data platforms and storage systems (Azure or similar cloud platforms preferred).
Experience working with datasets for machine learning systems, ideally including multimodal data.
Strong programming skills in Python and familiarity with modern data engineering tools and workflows.
Experience working with high-volume data ingestion, data processing pipelines, and dataset versioning.
Familiarity with robotics data pipelines or ROS2-based ecosystems is beneficial but not required.
Strong problem-solving skills and the ability to collaborate effectively with cross-functional technical teams.
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