Penguin LLM Trainer Roles (Multiple Languages) 2+

What does day-to-day look like :

Design multi-turn conversations that simulate real interactions between users and AI assistants using apps like calendar, email, maps, and drive.

Emulate both the user and the assistant, including the assistant's tool calls (only when corrections are needed).

Carefully select when and how the assistant uses available tools, ensuring logical flow and proper usage of function calls.

Craft dialogues that demonstrate natural language, intelligent behavior, and contextual understanding across multiple turns.

Generate examples that showcase the assistant’s ability to gracefully complete feasible tasks, recognize infeasible ones, and maintain engaging general chat when tools aren’t required.

Ensure all conversations adhere to defined formatting and quality guidelines, using an internal playbook.

Iterate on conversation examples based on feedback to continuously improve realism, clarity, and value for training purposes.

Collaborate with peers and reviewers to maintain consistency and high standards in deliverables.

Requirements :

3+ years of overall professional experience in a technical or analytical field.

Experience in any programming language or tech stack is acceptable; a strong grasp of APIs, data formats (e.g., JSON), and logical thinking is more critical than specific toolsets.

Strong general technical reasoning skills and the ability to model real-world assistant behavior using tool-based APIs.

Ability to break down complex tasks and simulate realistic dialogues that reflect user expectations and assistant limitations.

Excellent written communication skills in English, with a focus on clarity, tone, and instructional coherence.

Creativity and attention to detail in crafting realistic scenarios and responses.

Experience working with or around LLMs, virtual assistants, or function-calling frameworks is a plus.

Ability to follow detailed guidelines and formatting standards with high consistency.