Skip to main content
Tallo logoTallo logo

Research Scientist Post Training — AfterQuery

Job

David Joseph & Company

San Francisco, CA (In Person)

$200,000 Salary, Full-Time

Posted 2 days ago (Updated 1 day ago) • Actively hiring

Expires 6/21/2026

Apply for this opportunity

This job application is on an outside website. Be sure to review the job posting there to verify it's the same.

Review key factors to help you decide if the role fits your goals.
Pay Growth
?
out of 5
Not enough data
Not enough info to score pay or growth
Job Security
?
out of 5
Not enough data
Calculating job security score...
Total Score
100
out of 100
Average of individual scores

Were these scores useful?

Skill Insights

Compare your current skills to what this opportunity needs—we'll show you what you already have and what could strengthen your application.

Job Description

Research Scientist
  • Post Training — AfterQuery David Joseph & Company San Francisco, CA Job Details Full-time $150,000
  • $250,000 a year 5 hours ago Qualifications Research design Experimental design Model training Model evaluation Full Job Description Research Scientist
  • Post Training —
AfterQuery Location:
San Francisco, CA (Onsite)
Compensation:
$150,000
  • $250,000 base | $250,000
  • $450,000 total comp + equity About AfterQuery AfterQuery is an AI infrastructure company building training data and evaluation systems used by leading frontier AI labs.
They work directly with top labs to improve model performance through high-signal datasets and experimentation. $30M raised at ~$300M valuation. Founding team from Jane Street, Citadel, Google, Goldman Sachs, and Stanford AI Lab. About the Role This is a post-training research role focused on proving that data drives measurable improvements in model performance. You will design and run controlled experiments to isolate the impact of datasets on LLM behavior — working directly at the edge of model development. The focus is not theoretical research but building, running, and validating experiments that produce clear, defensible results tied to model capability improvements. What You'll Own Design and run controlled SFT and RL experiments to measure dataset impact on model behavior Isolate performance improvements across reasoning, tool use, long-horizon tasks, and domain workflows Quantify lift and performance changes across capabilities; interpret messy experimental results Prove that specific datasets lead to measurable improvements under defined conditions Translate results into clear, defensible outputs for partner AI labs Collaborate with internal teams to iterate on dataset quality and build shared experimental infrastructure Communicate findings directly with partner AI labs; support relationship building and revenue through validated results Requirements Strong familiarity with LLM training and evaluation methods including SFT and RL post-training Ability to design and execute lightweight experiments quickly Strong analytical instincts with ability to work through messy data Comfort working across domains including finance, software, policy, and enterprise workflows Bias toward building and execution over theory Undergraduate or master's research background preferred Nice to Have Experience at RL environment companies, AI safety organizations, or benchmarking groups Experience running controlled training experiments end to end Published work in model evaluation, post-training, or data curation Strong software engineering skills alongside research experience This Role Is NOT For Pure research profiles without hands-on execution or shipping experience Those who prefer narrow domain focus Candidates unable to operate in ambiguous, experimental environments Logistics Role is fully onsite in San Francisco — please only apply if you can commit to this Multiple headcount with strong hiring demand Shortlisted candidates will be contacted by David Joseph & Co. , the recruiting partner managing this search on behalf of AfterQuery.

Similar jobs in San Francisco, CA

Similar jobs in California