Experience building production-ready pipelines using Spark.
Ownership in ambiguity - Comfortable designing systems with incomplete requirements and willing to pivot fast if needed as the team is still discovering market fit and use cases.
Nice to Haves:
Computer vision ML systems: Experience productionizing CV models (segmentation, object detection) from training to inference at scale
Geospatial pipelines: Familiarity with imagery processing for maps (aerial, street-level), geometric algorithms, or map data workflows
Startup mentality: Thrives in greenfield environments with a bias towards action.
What You'll Be Doing:
Build end-to-end ML extraction pipelines to extract maps features from imagery using computer vision techniques, partnering with the team's ML engineers.
Design and implement data ingestion systems for aerial and street-level imagery sources
Develop operator workflows to ingest extracted features into the uber map
Prototype new extraction use cases (building entrances, parking zones, road metadata)
Perks and Benefits:
Uber's mission is to reimagine the way the world moves for the better
Offices continue to be central to collaboration and Uber's cultural identity
Opportunity to work on ML-based projects for maps and autonomous vehicle navigation