About OpenTrain
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About This Role
OpenTrain is recruiting a Quantitative Finance AI Training Expert to evaluate and compare model outputs on rigorous finance problems. You will work with a leading AI research lab to help train frontier generative models by judging responses, explaining strengths and weaknesses, and providing written feedback the research team uses to improve model behavior.
• Type: Contractor, part-time
• Hours: 20+ hours per week
• Pay: $150 USD per hour (hourly rate fixed)
• Work location: 100% remote — worldwide (English required)
• Data type: Text; label types: RLHF and evaluation/rating
• What You’ll Do
This is evaluation and RLHF-style rating work focused on quantitative finance. You will read model outputs and their reasoning, compare paired responses, and record which answer better demonstrates correct, robust quantitative thinking.
• Compare two AI-generated responses to the same prompt and choose the better answer
• Read and assess each model’s chain-of-thought or stated reasoning to inform judgments
• Explain why one output outperforms the other, citing methodological soundness and correctness
• Provide clear written feedback the research team uses to refine models
• Participate in onboarding and specialty calibration sessions to align evaluations
Requirements
You must meet the core professional and technical requirements below. The role emphasizes domain expertise, quantitative rigor, and clear written communication.
• 2+ years professional experience in quantitative finance (hedge fund, quant trading, derivatives, risk, or equity research)
• Advanced degree (MS/PhD) in Financial Engineering, Mathematics, Statistics, Physics, Economics, or equivalent industry experience
• Comfortable programming in Python for modeling and analysis (NumPy, pandas)
• Excellent written communication and high attention to detail
• Ability to commit 20+ hours per week and participate in onboarding/calibration
Who Should Apply
Apply if you are a quant, derivatives pricer, risk modeler, or research analyst who enjoys rigorous problem solving and can explain technical reasoning clearly in writing. This role is a good fit for people who want flexible, remote work that directly influences how state-of-the-art AI handles quantitative finance tasks.
• Ideal for professionals seeking part-time, high-impact work alongside other commitments
• Entry-level labeler classification reflects that this is evaluative work rather than a full-time research hire
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