Role OverviewAs a Research Engineer, you will build automated systems to verify and assure data quality in a decentralized marketplace, ensuring quality at scale to unlock high-value data sources. You will start by digging into the data manually to understand failure modes, then design systems to automate quality checks at scale, combining rule-based approaches with AI for fuzzier cases and human-in-the-loop review where it makes sense.
What You Will Do
Identify data quality issues, perform initial manual data quality review, build systems to automate quality checks at scale, design hybrid systems, and continuously improve verification methods.
Why It Might Be a Fit
This role requires a deeply technical individual with a strong learning slope, background in AI/ML engineering or software engineering at an AI-focused company, and ability to reason about likely data quality problems from first principles.
Requirements
- Deeply technical, with a strong learning slope and the ability to ramp quickly in a fast-moving field
- Background in AI/ML engineering, or software engineering at an AI-focused company with visible data ingestion and processing experience
- Ability to reason about likely data quality problems from first principles
- Comfortable owning ambiguous, open-ended problems end to end
- Comfortable working in person, full-time, in a San Francisco office
Benefits
- $140K-$250K base, plus equity
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