Designing Provenance Systems for AI Products

Senior Machine Learning Engineer - Content and Contributor Intelligence (Hybrid - United States) Yelp engineering culture is driven by our values: we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. All new engineers deploy working code their first week, and we strive to broaden individual impact with support from managers, mentors, and teams. At the end of the day, we’re all about helping our users, growing as engineers, and having fun in

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Covered skills: AI fundamentals Machine learning

Skills to close: None listed

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1. Capture Mechanisms for Content Origin

Build systems that record source context, device metadata, and model involvement at the moment of content creation or ingestion.

Implement systems that track edits, generations, compressions, and retrieval steps as content moves through your product.

3. Integrity Verification and Tamper Detection

Design mechanisms that validate provenance chains and detect when content or metadata has been altered outside recorded transformations.

4. User-Facing Provenance Displays

Translate technical provenance metadata into trust signals and decision-relevant cues that users can act on.

5. Provenance in Retrieval-Augmented Generation

Build citation and source-tracking systems that distinguish retrieved facts from model-generated inference in RAG pipelines.

6. Provenance Across Edge, Mobile, and Cloud

Architect provenance systems that balance on-device logging, cloud auditability, and performance constraints across distributed systems.

7. Provenance for Enterprise and Compliance

Design audit-ready provenance systems for knowledge management, legal workflows, and regulated industries.

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