
Sepal AI empowers ambitious AI teams to build faster and safer foundational AI models by providing expert-grounded data at every stage of development. They focus on accelerating model iteration and ensuring quality through rigorous vetting and a vast pool of specialized PhD-level experts. Their services include providing novel training datasets, custom benchmarks, pre-launch testing, and agentic applications, all supported by a human-centric approach to AI development. Sepal AI is SOC 2 Certified and is relied upon by top AI labs that prioritize responsible and high-impact AI.

Sepal AI empowers ambitious AI teams to build faster and safer foundational AI models by providing expert-grounded data at every stage of development. They focus on accelerating model iteration and ensuring quality through rigorous vetting and a vast pool of specialized PhD-level experts. Their services include providing novel training datasets, custom benchmarks, pre-launch testing, and agentic applications, all supported by a human-centric approach to AI development. Sepal AI is SOC 2 Certified and is relied upon by top AI labs that prioritize responsible and high-impact AI.
What they do: Expert-grounded training data, RL environments, evaluation tooling, and model fine-tuning for frontier AI labs and enterprises
Headquarters: San Francisco, California, United States
Founders: Fedor Paretsky; Kat Hu
Stage / funding: Pre-Seed; raised a round announced Sep 25, 2024
Security / compliance: SOC 2 Certified
| Company |
|---|
Training data quality, model evaluation, and safety for large and frontier AI models
2024
Data and Analytics
500000 USD
“Y Combinator (lead/backing investor)”
Join Our AI Benchmarking Study for Data Scientists
Sepal is conducting a national research initiative to evaluate and benchmark AI systems for safety, reliability, and real-world analytical capability. We are recruiting experienced data scientists
to help define professional standards in statistical modeling, machine learning, data engineering, and applied analytics. Your expertise will directly shape how next-generation AI models are assessed and validated for high-stakes analytical work.
Sample of Reported Job Titles
Data Scientist -- Machine Learning Engineer -- Applied Scientist -- Quantitative Analyst -- Data Science Analyst
MUST-HAVE QUALIFICATIONS
-- 4+ years full-time experience as a data scientist or in a closely related analytical or modeling role
-- English language fluency
-- U.S. residency
-- Access to a laptop or desktop computer with reliable internet
--
Strong technical proficiency: ability to work with Python or R, handle large datasets, build models, and evaluate analytical outputs
-- Ability to follow detailed written instructions and complete online tasks independently
COMPENSATION AND LOGISTICS
-- Hourly pay:
$38–$104
per hour, with task-based bonuses depending on experience and fit
-- Paid bi-weekly based on tracked and approved hours
-- Fully remote participation; work on your own schedule as long as deadlines are met
-- Current employment in the field is not required
WHAT YOU WILL DO
-- Complete a brief background questionnaire outlining your technical experience and areas of specialization
-- Evaluate AI-generated code, statistical analyses, predictive models, and data interpretations for rigor, safety, and realism
-- Help design realistic and edge-case analytical scenarios across data cleaning, feature engineering, experimentation, model development, and error analysis
-- Provide expert insight into what constitutes high-quality versus low-quality analytical work in real-world organizational settings
WHY PARTICIPATE?
Your real-world analytical expertise is essential for assessing the safety and capability of emerging AI systems. By contributing, you help establish rigorous evaluation benchmarks while being compensated for your knowledge. High-performing contributors may be invited to participate in continued research cohorts or advisory roles in ongoing AI capability and safety assessments.
LIMITED AVAILABILITY
We are selecting a limited number of experienced data scientists for this cohort. Applications are reviewed on a rolling basis, and slots will fill quickly.