$150,000–$250,000 Per Year
Analysis Skills, Artificial Intelligence (AI), Benchmarking, Construction, Data Analysis, Data Modeling, Data Quality, Data Sets, Data Structures, Diversity, Experiment Design, Laboratory, Modeling Languages, Performance Modeling, Quantitative Research, Research Laboratory, Scientific Research, Training Data Sets
San Francisco, California
Research Scientist – Frontier Data — AfterQuery
Location: San Francisco, CA (Onsite)
Compensation: $150,000 – $250,000 base | $250,000 – $450,000 total cash (including profit sharing) + competitive equity
Visa Sponsorship: None available
Employment Type: Full-Time
Headcount: 2 open seats
About AfterQuery
AfterQuery builds training data infrastructure and evaluation systems used by frontier AI labs to improve large language models and next-generation AI systems. The company is post-Series A with a small, high-impact technical team, direct partnerships with top frontier AI labs, and a focus on training data quality, evaluation rigor, and post-training optimization — with direct model improvement impact.
About the Role
This is a hands-on applied research role focused on model behavior, data quality, evaluation design, and RL training systems. This is not a pure academic research seat. This is not theoretical ML research. This is a fast-moving experimental execution role where you design experiments that directly improve frontier AI systems.
Core ownership includes:
- Designing high-signal datasets and identifying model failure modes
- Data slicing strategy, benchmark design, and evaluation framework construction
- Reward signal design, RLHF pipeline support, and RLVR experimentation
- Annotator behavior modeling and dataset diversity measurement
- Alignment capability measurement and quantitative experimentation
- Translating frontier lab training objectives into concrete datasets
- Fast experiment iteration under ambiguity across domains including finance, software engineering, enterprise workflows, and policy-related reasoning
Requirements
- Strong quantitative research instincts with genuine curiosity about model behavior
- LLM training familiarity — RLHF understanding and RLVR familiarity
- Evaluation methodology fluency
- Research depth equivalent to a strong BS/MS researcher
- Ability to reason about how data structure changes model performance
- Lightweight experimentation ability and comfort with messy, incomplete data
- Cross-domain reasoning ability, fast iteration mindset, and builder mentality
Nice to Have
- RL environment company experience (METR, Artificial Analysis, or similar)
- AI safety organization or benchmarking organization exposure
- Evaluation methodology work, dataset curation, or annotator/reward modeling
- Lab research experience and alignment research adjacency
- SWE + research hybrid profile
This Role Is NOT For
- Pure theorists or PhD-only slow execution profiles
- Candidates who need clean specs or clean datasets to operate
- Profiles with low experimentation velocity
Compensation & Benefits
- $150,000 – $250,000 base salary
- Profit sharing — $250,000 – $450,000 total cash potential
- Competitive equity
- Bonus upside and founding team access
Interview Process
- Pending approval
- Initial screen
- Take-home
- Take-home review
- Onsite
- Offer
Logistics
- Role is fully onsite in San Francisco — please only apply if you can commit to this
- No visa sponsorship available
Shortlisted candidates will be contacted by David Joseph & Co., the recruiting partner managing this search on behalf of AfterQuery.