LLM Function-Call Dialogue Trainer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help people start and grow freelance careers teaching AI by centralizing specialized projects, tracking work across platforms, and building a portfolio contributors control.

For this role, OpenTrain is the hiring and contracting organization — you will work with our training team to produce examples that directly improve assistant behavior.

Why AI training matters

AI training (data labeling / annotation / human feedback) is the human side of building intelligent systems. Contributors create the examples and judgments that modern models learn from — everything from transcriptions and translations to multi-turn assistant conversations and tool-using behavior.

This work is typically remote and flexible, and it places contributors on the cutting edge of how AI assistants behave in real-world workflows.

The role

You will be an LLM agent function-call dialogue trainer who writes high-quality, multi-turn conversations used for fine-tuning and evaluating assistants. Your examples will show when an assistant should use function-calling tools, how to format calls, and when natural conversation suffices.

The data you produce will include feasible task completion, handling infeasible requests, and engaging general chat when tools are unnecessary.

• Work type: Contractor, part-time
• Weekly time: 20+ hours/week
• Data type: Text (dialogue / prompt-response writing)
• Label tasks: PROMPT_RESPONSE_WRITING_SFT and FUNCTION_CALLING

What you'll do

Create realistic, multi-turn dialogues that reflect common assistant workflows and user intents. You will play both user and assistant roles, inserting tool calls with correct structure and showing clear reasoning and flow.

Follow project formatting and quality guidelines and revise examples based on reviewer feedback to maintain consistency and high standards.

• Design multi-turn conversations for calendars, email, maps, drives, and similar app-based workflows
• Decide when and which function calls are appropriate and write correct call arguments (JSON-like structure expected)
• Demonstrate logical tool selection, stepwise task decomposition, and contextual understanding
• Collaborate with reviewers and revise examples to meet quality guidelines

Requirements

Candidates must meet the stated technical and experience requirements and be comfortable modeling tool-based assistant behavior in writing.

• 3+ years professional experience in a technical or analytical field
• Strong technical reasoning and ability to decompose complex tasks into conversational steps
• Familiarity with APIs, JSON, and logical task decomposition
• Excellent written English and instructional clarity
• Experience creating realistic multi-turn assistant conversations and understanding function-calling frameworks

Who should apply and nice-to-haves

This role fits people who enjoy writing clear instructional dialogues, thinking about step-by-step tool usage, and iterating with reviewers. Applicants with hands-on experience using virtual assistants, building prompts for LLMs, or working with function-calling tooling will be especially competitive.

Preferred but not required: prior exposure to LLMs, assistant frameworks, or technical documentation writing.

Logistics & how work is managed

OpenTrain will manage the project and reviewers. You must be available for at least 20 hours per week and follow project-specific formatting and quality rules.

This role is open to applicants located in the following countries: IN, PK, NG, KE, EG, GH, BD, TR, BR, MX. English-language fluency is required.

• Employment types: Contractor, Part-time
• Languages: English (required)
• Eligible countries: IN, PK, NG, KE, EG, GH, BD, TR, BR, MX