Responsibilities
• Explore how frontier AI models behave on coding, ML, and analysis tasks and find where they quietly get things wrong
• Turn discovered weaknesses into well-crafted tasks that are hard for models but fair to grade
• Write up findings clearly with evidence and reproducible steps
• Team up with task authors to close loopholes, shortcuts, and grading gaps
• Share insights with researchers and fellow experts to improve the benchmark

Requirements
• MSc or PhD in a STEM field, or equivalent practical experience in a research-heavy domain requiring data analysis and coding
• 1+ years of experience in a research, research-engineering, security, or AI-evaluation role
• Demonstrated ability to identify vulnerabilities, edge cases, or failure modes in LLMs or ML systems (via red teaming, adversarial testing, security research, or rigorous model evaluation)
• Working proficiency in Python and Git, with the ability to script your own probes and analyses
• Strong familiarity with LLM capabilities, limitations, and evaluation techniques
• Perfectionist mindset with high attention to detail, creativity in finding what others missed, strong written communication, and ability to work independently on ambiguous problems
• Ability to engage reliably for ~35 hours per week

Preferred
• Past experience in AI training, model evaluation, or benchmark/task authoring

How to Apply
Click "Apply" to be taken to the Mercor website. Complete your profile by uploading your resume and confirming your work location. Once verified, you will be matched to opportunities as they arise. Please note that this role cannot support H1B or STEM OPT candidates. Applying through our link supports WFH Bulletin as a referral partner, but you are welcome to apply directly if you prefer.