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. We are YC's fastest unicorn, valued at $3.2 billion. 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 ApplyMassive Opportunity: We are YC's fastest unicorn valued at $3.2 billion 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.
OverviewAfterQuery is hiring Research Scientists to design and publish rigorous evaluations for frontier AI systems. The role spans agentic, coding, and safety evaluations, as well as expert-domain evaluations involving applied AI in healthcare, STEM, finance, and related fields. You will own evaluation development end to end and collaborate across disciplines to turn important capability gaps into rigorous public research.
ResponsibilitiesLead the end-to-end design, validation, launch, and continuous improvement of frontier AI benchmarks.
Partner with researchers and domain experts to develop evaluations around meaningful model failures, gaps in existing coverage, and high-priority domains.
Analyze model capabilities and failure modes using rigorous experimental design and statistical methods.
Build reproducible evaluation systems, including harnesses, graders, and benchmark infrastructure.
Collaborate with researchers to post-train models and measure the resulting performance gains.
Communicate results through benchmark reports, technical articles, and research papers.
Strong record of publishing benchmarks or research papers.
Clear technical communication and strong scientific writing skills.
Commitment to experimental rigor, including baselines, ablations, statistical validity, and contamination controls.
Ability to take an ambiguous evaluation question from initial scoping through a reproducible public release.
Depth in agentic, coding, and safety evaluations or applied machine learning in an expert domain.
PhD in a related technical field.
Research publications at leading conferences or peer-reviewed journals.
Interest in multidisciplinary research and the creativity to combine methods and insights from AI, engineering, science, and other expert domains.
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
- Strong record of publishing benchmarks or research papers
- Strong technical communication and scientific writing skills
- Commitment to experimental rigor, including baselines, ablations, statistical validity, and contamination controls
- Ability to take an ambiguous evaluation question from initial scoping through reproducible public release
- Depth in agentic, coding, and safety evaluations or applied machine learning in an expert domain
- PhD in a related technical field
- Research publications at leading conferences or peer-reviewed journals
- Interest in multidisciplinary research and creativity combining AI, engineering, science, and expert-domain methods
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.
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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.
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Healthcare Strength — Employee materials indicate medical, vision, and dental insurance are provided. Job postings reference a comprehensive package consistent with standard coverage.
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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
What We Do
AfterQuery is an applied research lab curating data solutions to accelerate foundation model development.
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