Research Engineer

About the role

This YC-backed startup is developing infrastructure to help data creators convert and sell information directly to AI labs. You will lead the effort to verify data quality within a decentralized marketplace, ensuring that high-value inputs meet strict buyer standards.

Key facts

What you'll do

• Detect and diagnose data inconsistencies, ingestion errors, and formatting defects.
• Conduct hands-on reviews of datasets to categorize common failure patterns.
• Engineer scalable automated systems that utilize both rule-based logic and AI models to validate data.
• Architect hybrid workflows that integrate human-in-the-loop oversight with automated verification.
• Refine and update quality assurance methods as AI development tools and data requirements shift.

Requirements

• Proven technical background in AI or machine learning engineering, or software engineering experience at an AI company involving data processing.
• Ability to solve complex, ambiguous problems from the ground up.
• Capacity to analyze data quality challenges using first principles.
• Ability to work on-site in the San Francisco office full-time.
• Strong aptitude for rapid learning and adapting to a fast-paced environment.

Nice to have

• Experience managing unstructured or noisy datasets.
• Practical judgment regarding the balance between automated systems and human-in-the-loop intervention.

Skills & tools

• AI/ML engineering
• Data ingestion and processing
• Automated quality assurance systems
• Rule-based and AI-driven verification logic

Practical notes

This is the primary hiring focus for the company. Candidates must be prepared to work in person at the San Francisco location.