Academic Research Collaborator – Professors & PhDs
- Company: Mercor
- Location: US
- Type: Full Time
- Compensation: $80–$110/hr (USD)
- Experience: Senior Level
About This Listing
AI Training Jobs curates remote AI training, evaluation, and expert annotation roles from vetted hiring platforms. This listing covers a full time Academic Research Collaborator – Professors & PhDs role with Mercor (US). Listed compensation: $80–$110/hr (USD). Requirements and responsibilities below are summarized from the employer’s public listing; apply through the official link.
Position Summary
We are seeking Professors and PhD students across all academic disciplines — STEM (ML, Coding, Data Science, CS, Physics, Mathematics, Engineering, Statistics) as well as professional and quantitative domains (Finance, Accounting, Economics, Law, Business). This role involves AI model training and evaluation work, including writing and assessing MLOps tasks and solutions to generate high-quality training data for frontier AI systems. You'll design and validate challenging benchmark tasks to help surface and diagnose reasoning and problem-solving gaps in a target model. The work centers on building robust, real-world tasks with executable Python tests and then analyzing model/agent behavior. All applicants are expected to have working proficiency in Python.
Core Responsibilities
- Task Design and Development: Design challenging, real-world domain-specific problems drawn from your area of expertise (e.g., financial modeling, legal reasoning, econometrics, ML, coding, scientific computation) that serve as the foundation for agentic tasks. Problems should be constructed to target specific core capability loss failures identified in a frontier AI model.
- Spec & Golden Solution Generation: Integrate the problems into an Agentic development environment, preparing all necessary components using Python.
- Evaluation and Analysis: Evaluate the target model's performance on the tasks.
- Headroom Identification: Identify tasks where the target model fails to pass all tests, specifically classifying the failure as a logical reasoning failure.
Qualifications
- Current or retired professor, OR PhD student, in any of the following areas: STEM: ML, Coding, Data Science, CS, Physics, Mathematics, Engineering, Statistics, Biology, Chemistry, Professional / Quantitative: Finance, Accounting, Economics, Law, Business, Degree (or PhD in progress) from a top university in your field, Working proficiency in Python — applied in research, industry, GitHub, or coursework (not theoretical familiarity), Ability to engage reliably for at least 30 hours/week during weekdays (i.e. at least 6 hours/day during weekdays), Past experience in AI training, model evaluation and data annotation is preferred, Basic ability to work independently and manage one's time, Verbal and written communication skills, problem solving skills, and interpersonal skills.
