AI Training Data Infrastructure Research Engineer
Overview
Own data quality assurance systems for decentralized marketplace. Deliver automated verification at scale. Start by analyzing failures then design solutions balancing rule-based logic AI models and human review. Growth driven by rapid expansion.
What You'll Do5
- 1Identify data quality issues including inconsistencies formatting problems and ingestion challenges
- 2Perform initial manual data quality review to deeply understand failure modes
- 3Build systems to automate quality checks at scale using rule-based and AI-driven approaches
- 4Design hybrid systems that balance automation with human-in-the-loop review where appropriate
- 5Continuously improve verification methods as data landscape and AI tooling evolve
Requirements5
- 1Deeply technical background in AI ML engineering or software engineering at AI-focused company
- 2Visible experience with data ingestion and processing
- 3Ability to reason about data quality problems from first principles
- 4Comfortable owning ambiguous open-ended problems end to end
- 5Comfortable working in person full-time in San Francisco office
Salary Insight
Salary not disclosed in listing
Location
Required Skills
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