LLM Trainer - Agent Function call
Turing • Remote, Bangladesh, Brazil, Egypt, India, Kenya, Mexico, Nigeria, Pakistan, Turkey, Ghana
Education
Not stated
Type
Hourly
Listed
186d ago
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- Weekly hours
- 20–40 hrs/week
- Timezone overlap
- Partial overlap with US Pacific time required
- Contract length
- 6 weeks
About this role
From the Turing listing
About Turing:Turing is one of the world’s fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems. Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies. Role Overview:This position is within a project with one of the foundational LLM companies. The goal is to assist these foundational LLM companies in enhancing their Large Language Models. One way we help these companies improve their models is by providing them with high-quality proprietary data. This data serves two main purposes: first, as a basis for fine-tuning their models, and second, as an evaluation set to benchmark the performance of their models or competitor models. For example, in the case of Agent Completion (AC) data generation, your task will be to simulate high-quality multi-turn conversations between a user and a smart assistant that utilizes function-calling tools to accomplish user goals. You will craft these dialogues by playing both the assistant and the user, while simulating tool use where necessary to guide the assistant through complex decision-making and real-world reasoning scenarios.
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
- 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.
- 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.
- 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.
- 3+ years of overall professional experience in a technical or analytical field.
Perks of Freelancing With Turing
- Work in a fully remote environment.
- Opportunity to work on cutting-edge AI projects with leading LLM companies.
Offer Details
- Commitments Required: At least 4 hours per day and minimum 20 hours per week with overlap of 4 hours with PST. (We have 3 options of time commitment: 20 hrs/week, 30 hrs/week or 40 hrs/week)
- Engagement Type: Contractor assignment (no medical/paid leave)
- Duration of Contract: 6 Weeks Location: India, Pakistan, Nigeria, Kenya, Egypt, Ghana, Bangladesh, Turkey, Brazil, Mexico
How long hiring takes
Across the AI training platforms we refer candidates to, the median gap between referral and hire is about 30 days. It varies by platform and role, so treat it as a rough guide for this one.
Interview Prep
This listing calls for these tools directly. Prep for the technical screen:
What to Expect
Looking at Turing Software Engineering listings we've tracked, contracts in this domain typically run about 8.4 weeks. Actual length varies by project, but this gives you a realistic baseline going in. This listing's 6-week contract is shorter than the typical 8.4-week Turing Software Engineering engagement.
Based on 28 extracted Turing Software Engineering listings.
Why this role
This LLM Trainer role covers building and evaluating agent function-calling tasks. The evaluation tests whether AI models correctly structure and invoke function calls, a narrower and more mechanical check than grading open-ended text generation.
Skills and categories
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Common questions
How does Turing's talent matching work?
Turing calls it the Intelligent Talent Cloud. You build a profile and go through vetting (automated tests, an AI-powered interview, practical skill assessments), and once vetted, Turing's algorithm surfaces your profile directly to partner companies like Fortune 500s and top AI labs. You don't browse listings or bid on work; matches come to you.
How and when does Turing pay contractors?
Monthly, in USD, via Deel, Payoneer, or direct bank transfer. You're engaged as an independent contractor responsible for your own local taxes. Plan your cash flow around a monthly cycle if you're used to weekly payouts elsewhere.
What does task-based AI training work look like?
Practical, hands-on data work: recording short videos, categorizing images, rating text responses, or analyzing data. Tasks are designed to be short and distinct, typically 5 to 60 minutes each.
What does Software Engineering work look like for a LLM Trainer - Agent Function call?
Tasks here are scoped to Software Engineering, not generic labeling. As a LLM Trainer - Agent Function call, expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Software Engineering) rather than following a one-size-fits-all rubric. If you don't have hands-on Software Engineering background, this is likely not the right listing to start with.
What specific skills does this listing call for?
Python, Java, JavaScript, and Coding are named directly in the listing. If you don't have hands-on experience with these, expect the screening process to test for them directly rather than accepting adjacent experience as a substitute.
How many hours per week does this role require?
Based on the listing, this role is scoped at 20–40 hours per week, over roughly a 6-week contract. Treat this as a real commitment expectation, not a loose estimate.
How much does this specific role pay?
The listing doesn't state a rate. The $12–$30/hr shown here is our estimate from the role type and location (see /pay-methodology), so treat it as a rough guide and confirm the actual rate with the platform before committing time.
What happens when I click Apply on this listing?
You'll be taken to Turing's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.
Can I apply from outside Bangladesh, Brazil, Egypt and 7 other countries?
This specific role is open only to people based in Bangladesh, Brazil, Egypt, India, Kenya, Mexico, Nigeria, Pakistan, Turkey, and Ghana. If you are somewhere else, applying is unlikely to lead to an offer even if you pass the assessment, because the restriction is usually about where the work can legally be contracted rather than your skills. Read the full description for any tax-residency or right-to-work caveats before you apply, since they can differ by country.