Quality Control Lead

Posted 10 Hours Ago
Be an Early Applicant
San Francisco, CA, USA
In-Office
150K-275K Annually
Mid level
Artificial Intelligence • Big Data
The Role
Owns final quality reviews for datasets containing code, technical, reasoning, and knowledge-work data. Leads QC processes and tooling, partners with infrastructure engineers to automate workflows, identifies systemic quality issues, provides feedback to contributor training, and reports quality metrics, error rates, root causes, and trends to leadership. The role also supports cross-functional operational initiatives in a fast-moving AI research environment.
Summary Generated by Built In
About AfterQuery

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. Since raising our $30M Series A at a $300M valuation, AfterQuery has grown well over a $100M revenue run rate. 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.

Why Apply
  • Massive Opportunity: We are one of the fastest-growing YC companies in our batch, and we believe we can become one of the fastest-growing YC companies of all time.

  • 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.

Key Responsibilities

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.

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

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

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

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

Required Qualifications
  • 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

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

Company Benefits (For Eligible Employees):
  • Health Insurance: Medical, Vision, Dental

  • 401(k) with Employer Match

  • Daily Meals: Daily UberEats Stipend

  • Monthly Wellness Stipend

  • Commute Covered

We are an equal opportunity employer committed to providing a workplace free from discrimination and harassment. Employment decisions are made without regard to legally protected characteristics under applicable federal, state, or local law. We comply with applicable pay transparency requirements and provide compensation ranges based on the position, qualifications, experience, and other relevant factors. Reasonable accommodations are available to qualified individuals with disabilities and for sincerely held religious beliefs, as required by law. This job description is intended to describe the general nature and level of work performed and is not an exhaustive list of all duties, responsibilities, qualifications, or working conditions associated with the position. We reserve the right to modify this job description as business needs change.

Skills Required

  • 3+ years of experience in a technical role such as software engineering, data science, ML engineering, or similar
  • Hands-on proficiency in at least one modern programming language
  • Ability to review, debug, and evaluate code, technical data, and knowledge-work data for correctness, structure, and quality
  • Experience reviewing others’ work with rigor
  • Experience building or leading a quality assurance or 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, including translating technical quality issues into actionable feedback for distributed teams
  • High agency and strong work ethic; comfort operating with minimal direction in ambiguous, fast-moving environments
  • Passion for AI and an entrepreneurial inclination
  • Demonstrated competitive success
  • Experience in AI training data, RLHF, or data-annotation quality assurance
  • Experience reviewing datasets across code, reasoning, and knowledge-work domains
  • Experience designing rubrics, grading criteria, or automated quality-check tooling and scripts
  • Familiarity with Claude Code or similar AI-assisted workflow tools
  • Computer science degree or equivalent hands-on engineering background

AfterQuery Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AfterQuery and has not been reviewed or approved by AfterQuery.

  • Fair & Transparent Compensation Pay is considered attractive when work is accepted, with public role postings and materials indicating strong compensation across expert projects and core employee roles. The experts track also highlights transparent pay rates and approval-linked payouts that do land.
  • Healthcare Strength Employee materials indicate medical, vision, and dental insurance are provided. Job postings reference a comprehensive package consistent with standard coverage.
  • Wellbeing & Lifestyle Benefits Daily meal stipends, commute support via Uber credits, and a monthly wellness stipend (including gym membership coverage) are prominently advertised. These lifestyle perks suggest attention to day-to-day convenience and wellbeing.

AfterQuery Insights

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The Company
200 Employees
Year Founded: 2024

What We Do

AfterQuery is an applied research lab curating data solutions to accelerate foundation model development.

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