Quality Control Lead

AfterQuery is an applied research lab curating data solutions for foundation model development. We serve every frontier AI lab with the mission of delivering the best data to power the best models. In doing so, we can make expertise that once took a lifetime to build available to anyone who needs it.

Our customers are the ones building the foundation models themselves and our work sits directly in the loop of how those systems improve. This is a rare opportunity to join a company at a defining moment in AI. Forbes reported that we could be YC's fastest unicorn, reportedly raising at a $3.2 billion valuation. We're based in San Francisco and backed by leading investors including Altos Ventures, BoxGroup, and Y Combinator and angels from Google DeepMind, OpenAI, Anthropic, Meta Superintelligence Labs, and Microsoft AI.

Massive Opportunity: Forbes reported that we could be YC's fastest unicorn, reportedly raising at a $3.2 billion valuation, and we're not slowing down.

Founding Impact: You will own and architect core infrastructure systems that power our platform from the ground up.

Equity & Growth: Competitive salary and meaningful equity. As we scale, you’ll have the opportunity to shape the engineering organization and lead major technical initiatives.

Strong Team: Our founding team has experience from Citadel Securities, Meta, Google, Silver Lake, and Morgan Stanley — work alongside world-class engineers and researchers.

We're looking for a Quality Control Lead to own the final checkpoint between raw data and delivered product. You'll be the person who decides what's good enough to ship, the coach who helps contributors get better, and the builder who automates away the errors that shouldn't happen twice.

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  Final Quality Review: Own the last quality checkpoint before datasets are delivered or published, auditing outputs (including code, technical, and reasoning data) for correctness, clarity, structure, and adherence to spec.

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  QC Process & Tooling: Work with infrastructure engineers to continuously automate and improve QC workflows

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  Cross-Functional Feedback Loop: Partner with data delivery teams to identify systemic quality issues, feed corrections back into contributor training, and prevent recurrence.

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  Metrics & Reporting: Own quality metrics and KPIs, reporting on error rates, root causes, and improvement trends to company leadership.

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  Operational Support: Contribute to company-wide initiatives across building, analysis, coordination, and execution as AfterQuery scales.

• 3+ years of experience in a technical role (software engineering, data science, ML engineering, or similar) with hands-on proficiency in at least one modern programming language

• Proven ability to review, debug, and evaluate both code and technical data and knowledge work data for correctness, structure, and quality; demonstrated rigor in reviewing others' work

• Experience building or leading a quality assurance/quality control function, ideally for a technical or data-centric product

• Extremely high attention to detail and comfort making judgment calls on ambiguous or contested technical content

• Strong leadership and communication skills; able to translate technical quality issues into clear, actionable feedback across a distributed team

• High agency and strong work ethic; comfort operating with minimal direction in ambiguous, fast-moving environments

• Genuine passion for AI and an entrepreneurial inclination

• Demonstrated competitive success

• Experience in AI training data, RLHF, or data-annotation quality assurance

• Background reviewing datasets across multiple domains (code, reasoning, knowledge work)

• Experience designing rubrics, grading criteria, or automated quality-check tooling/scripts

• Familiarity with Claude Code or similar AI-assisted workflow tools

• Computer science degree or equivalent hands-on engineering background