AfterQuery

Software Engineer - RL Environments

San Francisco

Sponsorship not specifiedDetected 99 days ago

Data StructuresData EngineeringValuationResearchLab Research

About the role

You'll go from hypothesis to live experiment quickly, and your output will feed directly into model training runs at scale.

Design data slides and explore data shapes that expose meaningful model failure modes across domains like finance, code, and enterprise workflows
Build and refine evaluation rubrics and reward signals for RLHF and RLVR training pipelines
Develop quantitative frameworks for measuring dataset quality, diversity, and downstream impact on model alignment and capability
Create and manage both real world & synthetic data pipelines
Partner with lab research teams to translate their training objectives into concrete data and evaluation specifications
Genuine obsession with how data structure, selection, and quality drive model behavior
Ability to design lightweight experiments, move fast, and extract actionable insights from messy results
As a SWE (Environments), you will design the datasets and evaluation rubrics that directly influence how frontier models learn.

Major plus if they've worked for/interned for any RL environment companies in the past or any AI safety or benchmarking orgs like METR, Artificial Analysis, etc..
Former founders and early engineers at early stage startups are a plus.
We don't filter on pedigree.
We want people who can demonstrate they work hard, learn fast, and care deeply about getting the details right.

AfterQuery https://www.afterquery.com/ is an applied research lab curating data solutions for foundation model development.
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.

This listing is sourced directly from AfterQuery's careers page and normalized into a canonical job model.