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Machine Learning Engineer - Quality Intelligence
Afterquery
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About this role
ABOUT AFTERQUERY
AfterQuery https://www.afterquery.com/ 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
AfterQuery builds the data and evaluation systems that power frontier AI models. Every leading AI lab uses our datasets and reinforcement learning environments to encode and scale real-world expertise.
We’re hiring a Founding Machine Learning Engineer, Quality Intelligence to build the ML systems behind how we measure, improve, and scale data quality. You’ll work on production systems at the intersection of machine learning, human expertise, and frontier model evaluation.
This role is for someone who wants to build practical ML systems that directly improve the quality, reliability, and scalability of expert human data.
RESPONSIBILITIES
Build ML and data systems that help measure quality across complex human data workflows
Develop systems for expert matching, quality prediction, and anomaly detection
Build evaluation infrastructure for tasks, reviewers, projects, and data deliveries
Turn messy real-world signals into models, metrics, and product improvements
Partner with engineers, domain experts, and operators to improve how high-quality data is created and reviewed
Own high-impact systems from early design through production deployment
REQUIRED QUALIFICATIONS
3-6 YOE with relevant experiences
Strong software engineering background with experience shipping production systems
Experience with applied ML, ranking, recommendations, search quality, marketplace systems, trust/safety, fraud, or data quality systems
Strong data intuition and ability to work with messy, ambiguous real-world signals
Comfort working across backend systems, data pipelines, ML models, and internal tools
Ability to move quickly in a high-ownership, fast-changing environment
Deep care for quality, precision, and customer impact
NOT A FIT IF
- You want to do pure research without owning production systems
- You only want to train models and not build product infrastructure
- You need clean datasets and perfectly scoped problems
- You do not want to work closely with users, operators, and domain experts
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.
Salary insight
The midpoint of this range ($250k) is about 25% above the median disclosed salary for San Francisco roles listed on ForgeApply ($200k across 8,649 jobs).
See full Machine Learning Engineer salary data for San Francisco →
Based on live postings with disclosed pay on ForgeApply; refreshed daily. Not an estimate of this employer's offer.
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