
Penguin LLM Trainer Roles
1 week ago
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.
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