Data Engineer (ML Platform & Data Foundations) at Intuitive

Primary Function of Position We are looking for a Data Engineer to build and own the data foundations that power machine learning and analytics, with a strong focus on image or and video data. This role is focused on designing pipelines to ingest, process, and organize large-scale visual datasets for machine learning applications . You will work closely with ML scientists, data scientists, and software engineers to ensure data is reliable, discoverable, and production ready. What Success Would Look Like: • ML scientists can easily access trusted, well-organized image and video datasets-documented data • Data pipelines are reliable, observable, and scalable • Data quality issues are detected early and resolved quickly • The data platform accelerates ML development and deploymentEssential Job Duties • Data Platform & Pipelines • Build and maintain data pipelines for image and video datasets used by ML models • Handle visual data ingestion, processing, validation and storage across system • Extract and organize large media files and related metadata • Optimize data systems for performance and reliability including handling large binary data • Debug and fix issues in data pipelines and datasets • Data Organization & Quality • Organize datasets so they can be reliably used for model training and evaluation • Define and maintain schemas, metadata, and data documentation • Implement data quality checks, validation frameworks, and monitoring • Support data versioning, lineage, and reproducibility across evolving datasets • ML Enablement • Partner closely with ML scientists to understand data requirements • Prepare and maintain datasets used for training and testing models • Support ML workflows by ensuring consistent, high-quality data inputs • Enable smooth handoff from experimentation to production • Collaboration & Standards • Collaborate with product, analytics, and engineering teams to align data solutions with business needs • Establish best practices for data modeling, pipeline design, and governance • Contribute to architectural decisions for data and ML platforms