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Conduct a semester-long applied AI research project with an AfterQuery mentor in areas such as data quality, post-training, agent and foundation-model evaluation, or public benchmarks. Responsibilities include formulating research questions, designing experiments, developing datasets and evaluation methods, analyzing results, documenting reproducible work, and co-authoring a publication. Scholars receive mentorship, engineering support, annotation resources, and compute access.

Support research scientists with experiments involving advanced reasoning, computer use, and agentic AI models. Interns will collect, process, and analyze proprietary datasets; develop and test algorithms; document findings; present research; and collaborate with interdisciplinary teams. The role offers opportunities to contribute to publications and work with specialized datasets and computational resources. Interns work 10–40 hours weekly depending on company needs.

Designs, validates, launches, and improves rigorous evaluations and benchmarks for frontier AI systems. The role analyzes model capabilities and failure modes using experimental and statistical methods, builds reproducible evaluation infrastructure, collaborates on post-training measurement, and communicates findings through reports, technical articles, and research papers.

Lead strategic projects for AI data solutions, managing client relationships, specialized expert teams, dataset specifications, and end-to-end execution. Coordinate contributors across technical and professional domains while supporting operational initiatives that influence foundation model training and evaluation. The role requires advanced STEM expertise, quantitative reasoning, scientific research experience, strong leadership, entrepreneurial initiative, and familiarity with data-analysis programming and LLM workflows.

Corporate Counsel will serve as AfterQuery’s first in-house legal hire, managing commercial contracts, data licensing, DPAs, employment agreements, labor-law guidance, worker classification, and HR compliance. The role partners with Sales, Finance, and People teams, triages business legal questions, maintains contract templates, and coordinates with outside counsel on specialized matters including export controls, financing, and privacy investigations.

Build end-to-end product experiences supporting expert acquisition, onboarding, assessment, matching, activation, and retention. Partner with Growth and Operations to identify bottlenecks, instrument funnels, run experiments, and improve measurable outcomes. Develop internal tools and automation, create durable product primitives, and make thoughtful tradeoffs among speed, reliability, and maintainability while working closely with founders and cross-functional teams.

Lead AfterQuery’s enterprise data acquisition strategy, identify and prioritize target data assets, negotiate high-value purchase and licensing agreements, manage data partners, and ensure legal, IP, governance, and technical requirements are met. Own acquisition budgets, pipelines, forecasting, and ROI reporting while collaborating with Engineering, Operations, Legal, and Research to package data for foundation model training.

Lead strategic projects for leading AI organizations, managing client relationships and specialized expert teams. Define dataset specifications that influence foundation-model training and evaluation, own projects from scoping through delivery, and support high-impact operational initiatives. The role requires structured problem-solving, quantitative analysis, strong communication, entrepreneurial initiative, and comfort operating independently in an ambiguous, fast-moving environment.

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.

Run full-cycle recruiting for business and operations roles, including sourcing, screening, interviewing, candidate closing, and talent pipeline development. Partner with business leaders and the executive team to define hiring profiles, prioritize searches, improve interview rubrics and scorecards, support candidate experience, and track recruiting funnel performance. The role requires recruiting high-caliber candidates from finance, consulting, private equity, technology, and related fields in a fast-paced, five-day in-office San Francisco environment.