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Freelance Tax Accountant - AI Trainer

Job in New York, New York County, New York, 10261, USA
Listing for: Mindrift
Contract position
Listed on 2026-01-01
Job specializations:
  • Software Development
    AI Engineer
Salary/Wage Range or Industry Benchmark: 73 USD Hourly USD 73.00 HOUR
Job Description & How to Apply Below
Location: New York

This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.

What We Do

At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI. The Mindrift platform connects specialists with AI projects from major tech innovators, unlocking the potential of Generative AI by tapping into real‑world expertise from across the globe.

Who We're Looking For

We are seeking curious, intellectually proactive contributors—people who double‑check assumptions and play devil's advocate. Are you comfortable with ambiguity and complexity? Does an async, remote, flexible opportunity sound exciting? Would you like to learn how modern AI systems are tested and evaluated? This flexible, project‑based opportunity is well suited for those who thrive in such environments.

About the Project

You will create complex, realistic tasks that push frontier AI agents to their limits. Think scattered data, conditional procedures, and genuine domain expertise. You'll build a detailed version with objective scoring, then write an ambiguous version intended to train the agent to succeed with less hand‑holding—real expert complexity only. By doing so, you’re improving the AI tools you’ll eventually use yourself.

Responsibilities
  • Design and develop realistic, high‑complexity tasks for AI agents.
  • Create detailed version of tasks with objective scoring.
  • Write ambiguous version to train agents for less hand‑holding.
  • Collaborate with quality team to refine prompts and model responses.
Requirements
  • Bachelor's or Master's Degree in Accounting, Auditing, Financial Accounting, or closely aligned areas.
  • Professional industry experience in accounting with a minimum of 3 years in relevant fields (e.g., audit, financial reporting, internal controls, tax, management accounting). Experience in cross‑functional, applied, or international projects is an advantage.
  • Having a chartered accountancy qualification such as CPA, ACCA, or ICAEW is an advantage.
  • Familiarity with US GAAP standards.
  • Ability to write clearly and professionally, including explaining complex tasks in simple, structured language.
  • Ability to analyze and synthesize information from multiple sources and turn it into accurate, coherent outputs.
  • Creativity in designing realistic and engaging examples, cases, or workflows based on domain knowledge.
  • Proven ability to use English fluently in professional settings, written and verbal (C1/C2 level).
  • Access to a laptop, stable internet connection, and sufficient availability to engage with project tasks.
  • Motivation to work with challenging, complex, but well‑defined guidelines, learn new methods, and strengthen domain‑specific skills.
Benefits
  • Get paid for your expertise, with rates that can go up to $73/hour depending on your skills, experience, and project needs.
  • Take part in a part‑time, remote, freelance project that fits around your primary professional or academic commitments.
  • Work on advanced AI projects and gain valuable experience that enhances your portfolio.
  • Influence how future AI models understand and communicate in your field of expertise.
How to Get Started

Apply to this post and get the chance to contribute to projects aligned with your skills, on your own schedule. To begin working in production, you’ll need to complete the qualification step and project onboarding, where you’ll get familiar with the guidelines interface and try your first real task with guidance from our quality team. From creating training prompts to refining model responses, you’ll be directly shaping how useful these models become for your own future work.

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