Retail Specialist

Mercor; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

Cincinnatus LLC's GenAI team seeks experienced Retail SMEs to evaluate AI outputs against rubrics and contribute to training data for foundational models.

You will guide researchers and engineers, design retail tasks, and provide detailed feedback on correctness and reasoning, while collaborating with other SMEs to ensure consistency and quality.

Qualifications

• 8+ years of dedicated professional experience in retail at top-tier organizations.
• Hands-on experience evaluating LLM/AI outputs against rubrics or structured scoring criteria.
• Demonstrable career progression in retail leadership roles.
• Ability to engage reliably for at least 35 hours/week during weekdays.
• Excellent verbal and written communication, problem-solving, and interpersonal skills.

Responsibilities

• Guide research and engineering teams to close knowledge gaps in retail merchandising, category management, and operations reasoning.
• Design challenging, domain-relevant retail tasks and write accurate, well-reasoned solutions grounded in real retail practice.
• Evaluate AI model outputs against structured rubrics and provide clear, written feedback on correctness, judgment, and reasoning quality.
• Develop and refine evaluation guidelines and scoring rubrics specific to retail tasks.
• Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

Skills

Retail domain expertise

LLM evaluation

Rubric-based assessment

Stakeholder collaboration

Job description

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.

1. Overview

Join a leading AI lab's cutting-edge GenAI team and help build foundational AI models from the ground up. We're seeking talented Retail subject‑matter experts (SMEs) with deep domain expertise and hands‑on experience evaluating AI model outputs against rubrics to bring rigor and real‑world retail judgment to our AI training data.

This is a W-2 employment position with Cincinnatus LLC, with the opportunity to be placed at a leading AI Lab as part of their extended workforce.

2. Key Responsibilities

• Guide research and engineering teams to close knowledge gaps in retail merchandising, category management, and operations reasoning.
• Design challenging, domain‑relevant retail tasks and write accurate, well‑reasoned solutions grounded in real retail practice.
• Evaluate AI model outputs against structured rubrics and provide clear, written feedback on correctness, judgment, and reasoning quality.
• Develop and refine evaluation guidelines and scoring rubrics specific to retail tasks.
• Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

3. Core Qualifications

• 8+ years of dedicated professional experience in retail (e.g., merchandising, category management, retail operations, buying/planning) at a recognized, top‑tier organization (e.g., Amazon, Walmart, Target, Nike, Costco, Home Depot, or equivalent).
• Prior hands‑on experience evaluating LLM/AI model outputs against rubrics or structured scoring criteria — mandatory; please describe this experience in your application.
• Demonstrable career progression (e.g., Category Manager - Senior Manager - Director of Merchandising).
• Ability to engage reliably for at least 35 hours/week during weekdays.
• Verbal and written communication skills, problem‑solving skills, and interpersonal skills.

Equal Employment Opportunity: 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.