Finance AI Model Evaluation Expert

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. We help skilled professionals find specialized freelance projects, build a unified AI-training portfolio, and grow into durable careers shaping how AI systems behave.

As the hiring and contracting organization for this role, OpenTrain connects you directly to meaningful evaluation work in a fast-growing industry where human judgment is essential to building safe, accurate AI.

About AI Training Work

AI training (also called data labeling or annotation) is the human side of AI development: people prepare, review, and rate examples that modern models learn from. This role focuses on evaluating model responses and improving evaluation methods so finance-focused LLMs produce reliable, accurate output.

Work in this field is often 100% remote, flexible, and accessible — it's a way to apply finance domain expertise directly to the next generation of intelligent systems.

The Role

We are seeking a Finance AI Model Evaluation Expert to review LLM performance on finance tasks, design rubrics for domain-specific judgments, and collaborate with AI researchers and finance practitioners to improve training strategies and benchmarks. The work centers on text evaluation and RLHF-style rating and feedback.

Typical examples of areas you'll influence include deal analysis, M&A assessments, investment analysis, forecasting and revenue builds, corporate finance, asset management, and risk evaluations.

• Job type: Contract, part-time (OpenTrain contracting)
• Data type: Text; label types: Evaluation/Rating, RLHF
• Duration: ~1 month with possible extension

What You'll Do

• Evaluate LLM outputs across finance domains where models perform poorly, providing clear, actionable ratings and feedback.
• Create well-structured rubrics and grading guidelines for tasks such as deal analysis, M&A assessment, investment case reviews, and forecasting checks.
• Document edge cases and common failure modes to guide model improvements and training data collection.
• Work closely with AI researchers and fellow finance experts to refine evaluation benchmarks and training strategies.

Requirements

• Minimum 2+ years of professional experience in finance or a related domain (capital markets, trading, portfolio management, accounting, investment banking, private equity, financial consulting, or quant roles).
• Strong grasp of financial concepts: investment analysis, forecasting, revenue builds, corporate finance, asset management, and risk management.
• Excellent written English with the ability to explain judgments clearly and concisely.
• Proven ability to create clear rubrics and evaluate nuanced LLM outputs in finance contexts.
• CFA, CA, CPA, or MBA in Finance is a plus (not required).

Commitment, Pay & Logistics

This is flexible freelance work you can do remotely. Typical commitment is 10–30 hours per week for about one month; extensions are possible depending on project needs. The project expects focused, reliable contributions during the agreed hours.

Compensation is competitive: around $100+ USD per hour, with final rates based on experience. The role is open worldwide and conducted in English.

• Work location: Remote, worldwide (English required)
• Hours: Flexible, typically 10–30 hrs/week
• Pay: About $100+/hour (hourly contractor)
• Employment type: Contractor, part-time

Who Should Apply & How It Works

Apply if you have hands-on finance experience, strong written communication, and interest in shaping how AI understands finance. This role is a great fit for practitioners who want short-term, high-impact work that directly improves model behavior in real finance tasks.

To apply, create a free OpenTrain account, complete your profile highlighting relevant finance experience, and submit your application. If selected, you'll be contracted through OpenTrain and onboarded with evaluation guidelines and sample tasks.

• Ideal applicants: finance professionals who enjoy detailed evaluation and clear documentation
• Onboarding: training materials and rubric templates provided; you'll start by rating sample outputs