Frontier AI Research Fellow — Paid 12–16 Weeks

AfterQuery; San Francisco (CA); On-site; USD 67,000 - 89,000; Full time

Benefits offered by this job

Health Insurance: Medical, Vision, & 0

401(k) with Employer Match

Daily UberEats Stipend

Monthly Wellness Stipend

Job summary

AfterQuery is seeking a Research Fellow to join its San Francisco office for 12–16 weeks of full-time, paid research. Fellows collaborate with experienced researchers to shape frontier AI projects, with mentorship and hands-on support from engineering, datasets, annotation, and compute resources.

Projects are tailored to expertise in data quality, post-training methods, and evaluation, with opportunities to co-author publications and contribute to public benchmarks.

Qualifications

• Significant research experience in academic, clinical, legal, or industry settings.
• Clear technical communication and strong scientific writing skills.
• A strong record of research or publication with reproducible results.
• Passion for advancing frontier AI and some understanding of model evaluation.
• Availability to work full time in San Francisco for 12-16 weeks.

Responsibilities

• Define and execute a full-time project with an AfterQuery mentor.
• Formulate research questions, design experiments, and analyze results.
• Develop datasets, methods, evaluations, or benchmark assets needed.
• Document methods and results and ensure reproducibility with teams.
• Co-author a paper and work toward publication.

Skills

Research experience

Technical writing

Data analysis

Publications

Model evaluation

Full-time availability

Education

PhD or equivalent

Late-stage PhD candidate

Tools

Python

Jupyter

Job description

AfterQuery is seeking a Research Fellow to join its San Francisco office for 12–16 weeks of full-time, paid research. Fellows collaborate with experienced researchers to shape frontier AI projects, with mentorship and hands-on support from engineering, datasets, annotation, and compute resources.

Projects are tailored to expertise in data quality, post-training methods, and evaluation, with opportunities to co-author publications and contribute to public benchmarks.