Curated opportunity · Reviewed 20 July 2026

LLM Trainer — Agent Function Call

Turing — Anthropic • Nvidia • Disney
Remote6 WeeksPay: Frontier AI

Opportunity overview

Turing places software and AI engineers with major companies on a project basis, including LLM-training work like agent function-calling — teaching a model to correctly trigger tools and APIs. Engagements are typically several weeks long rather than one-off tasks.

Who this may suit

Software engineers comfortable with technical interviews

Typical requirements

Usually a coding assessment plus a technical interview

Requirements can vary between projects or individual openings. Treat this summary as a starting point and use the destination page as the current source of truth.

What to check before applying

Brush up on tool-use and function-calling patterns specifically before the interview

Never pay HowToAIjob or an unknown recruiter to secure a role. Confirm the employer domain, eligibility, worker classification, rate basis and payment terms before sharing sensitive information.

Getting started with Turing — Anthropic • Nvidia • Disney

Best suited for: Software engineers comfortable with technical interviews. Before applying, check what the role typically expects: Usually a coding assessment plus a technical interview. Turing — Anthropic • Nvidia • Disney runs this as freelance, project-based work, which is the more common structure across human feedback jobs generally — expect a short entry assessment before you can start accepting paid tasks.

Where Turing — Anthropic • Nvidia • Disney fits among RLHF jobs

Turing places software and AI engineers with major companies on a project basis, including LLM-training work like agent function-calling — teaching a model to correctly trigger tools and APIs. Engagements are typically several weeks long rather than one-off tasks. Within the wider human feedback jobs category on this list, Turing — Anthropic • Nvidia • Disney is worth comparing against similar listings if you are cross-applying to several platforms rather than relying on a single source of income. Brush up on tool-use and function-calling patterns specifically before the interview. As with any platform in this space, treat advertised pay as a range tied to specific task types rather than a guaranteed flat rate, and re-check the official listing periodically since openings and availability change often.