Expert Professors - Coding & STEM

Join a leading AI lab’s cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models.

We are seeking Professors across STEM domains, including ML, Coding, Data Science, etc. to contribute to a project supporting a frontier-model evaluation effort focused on coding and agentic workflows. 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 tests and then analyzing model/agent behavior.

Location Requirements

1. Overview

Professors across STEM domains, including ML, Coding, Data Science, etc.

2. Key Responsibilities

3. Core Qualifications

About Cincinnatus LLC

Equal Employment Opportunity

Join a leading AI lab’s cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models. We are seeking Professors across STEM domains, including ML, Coding, Data Science, etc. to contribute to a project supporting a frontier-model evaluation effort focused on coding and agentic workflows. 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 tests and then analyzing model/agent behavior. This is a W2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI Lab as part of their extended workforce. You will join a team of domain experts and together, you will guide the next generation of frontier AI tools. Task Design and Development: Design challenging, real-world domain-specific problems 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, which include: Detailed Instructions and an overview of the required task. A Golden solution that follows the instruction. Any specific consultations and feedback with domain-specific knowledge. Evaluation and Analysis: Evaluate the cross model’s performance on the tasks Headroom Identification: Identify tasks where target model fails to pass all tests, specifically classifying the failure as a logical reasoning failure Loss Extraction: Analyze the agent’s steps (Agent Trajectory) to observe and extract core capability loss patterns from the model. Current or retired professor within STEM, including ML, coding, data science, etc. Degree in computer science, data science, or relevant STEM field 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 Cincinnatus LLC is an enterprise staffing company that partners with leading technology companies to source and employ highly skilled professionals for contingent and contract-based opportunities. Cincinnatus serves as the employer of record for these engagements, providing W-2 employment, payroll, benefits, and compliance, while placing employees directly within client teams to work on high-impact initiatives. Roles hired through Cincinnatus are not project-based or freelance engagements. They are structured, role-based positions that typically involve part-time or full-time commitments, close collaboration with a client's internal teams, and integration into standard enterprise workflows. Cincinnatus is a legal entity separate from Mercor. While opportunities may be discovered through Mercor's platform, employment, onboarding, payroll, and benefits for these roles are administered by Cincinnatus LLC. Cincinnatus is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or any other legally protected characteristic. Cincinnatus is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans throughout the job application process. We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

• Task Design and Development: Design challenging, real-world domain-specific problems 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, which include:

Detailed Instructions and an overview of the required task.

A Golden solution that follows the instruction.

Any specific consultations and feedback with domain-specific knowledge.

• Detailed Instructions and an overview of the required task.
• A Golden solution that follows the instruction.
• Any specific consultations and feedback with domain-specific knowledge.
• Evaluation and Analysis: Evaluate the cross model’s performance on the tasks
• Headroom Identification: Identify tasks where target model fails to pass all tests, specifically classifying the failure as a logical reasoning failure
• Loss Extraction: Analyze the agent’s steps (Agent Trajectory) to observe and extract core capability loss patterns from the model.
• Detailed Instructions and an overview of the required task.
• A Golden solution that follows the instruction.
• Any specific consultations and feedback with domain-specific knowledge.
• Current or retired professor within STEM, including ML, coding, data science, etc.
• Degree in computer science, data science, or relevant STEM field
• 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