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Research Technical Program Manager

On-site
AfterQuerySan Francisco, CA, US1 day agoWebsite
Fresh
Full-time
Research

Compensation

$210,000-$450,000/yr
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Description

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.

Overview

Your job is to make ambitious research programs move. You will own the execution of programs spanning post-training, enterprise post-training, fellowships, evaluation releases, and partner research. You will turn open-ended research goals into clear plans, keep researchers, engineers, SPLs and external partners aligned, and surface the decisions and blockers that matter. This is not a traditional project-management role. You must understand the technical work well enough to reason about experiments, datasets, evaluations, training pipelines, and research tradeoffs. Your impact will come from creating just enough structure for the team to run more programs, make better decisions, and ship high-quality work faster.

Responsibilities

Own planning and execution across post-training, enterprise post-training, fellowship, and public evaluation programs.

Translate ambiguous research objectives into milestones, owners, dependencies, success criteria, and decision points.

Maintain a trustworthy view of program health, including experiment progress, risks, blockers, partner dependencies, and upcoming releases.

Required Qualifications

2-4 years project/program management experience

Experience leading complex technical programs across research, machine learning, engineering, or data organizations

Working knowledge of the LLM development lifecycle, including data creation, SFT, RL-based post-training, and evaluation

Strong communication and an ability to turn messy technical information into clear decisions and next steps

Company Benefits (For Eligible Employees):

  • Health Insurance

    Medical, Vision, Dental

  • 401(k)

    With Employer Match

  • Daily Meals

    Daily UberEats Stipend

  • Wellness Stipend

    Monthly - Covers Equinox Membership

  • 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.

Stack

LLMsMachine LearningFoundation Models
Posted
Aug 27, 2026
Last seen
Aug 28, 2026
First seen
Aug 28, 2026

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