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AfterQuery is an applied research lab that curates data solutions for foundation model development, serving frontier AI labs with high-quality datasets to power the best models. The company is YC's fastest unicorn, valued at $3.2 billion, backed by leading investors including Altos Ventures, BoxGroup, Y Combinator, and angels from Google DeepMind, OpenAI, Anthropic, Meta, and Microsoft AI.
The Quality Control Lead will own the final checkpoint between raw data and delivered product, serving as both a quality arbiter and coach for contributors. This is a founding-impact role where you'll architect core QC infrastructure systems from the ground up.
Key responsibilities include:
- Owning the final quality review checkpoint before datasets are delivered or published, auditing outputs (code, technical, and reasoning data) for correctness, clarity, structure, and spec adherence
- Working with infrastructure engineers to continuously automate and improve QC workflows
- Partnering with data delivery teams to identify systemic quality issues, feeding corrections back into contributor training, and preventing recurrence
- Owning quality metrics and KPIs, reporting on error rates, root causes, and improvement trends to leadership
- Contributing to company-wide initiatives across building, analysis, coordination, and execution as AfterQuery scales
This role combines technical depth with leadership and operational scope. You'll translate quality issues into actionable feedback across a distributed team, design rubrics and grading criteria, and build automated tooling to prevent recurring errors.
REQUIREMENTS:
- 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 code, 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
PREFERRED QUALIFICATIONS:
- 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
