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Data Science

Generative AI Associate

innodata • Remote - United States, United States

Education

Bachelor

Type

Hourly

Pay Rate

$15/hr

Listed

166d ago

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About this role

From the innodata listing

Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers. Scope of the Role: At Innodata, we’re partnering with the world’s leading technology companies to build the future of generative AI and large language models (LLMs). We’re on the lookout for smart, savvy, and curious Generative AI Specialist to join our global contributor community as part of our Subject Matter Expert (SME) on Demand program. This is not a traditional full-time role. It’s a part-time, remote, flexible, project-specific opportunity designed for those who want to make a real impact—on their schedule. Whether you're a writer, linguist, educator, researcher, or just deeply passionate about language and logic, this role lets you contribute to cutting-edge AI development while maintaining control over your time. You’ll be helping LLMs learn the intricacies of language and reasoning—not just how to write, but how to think. If you’ve ever dreamed of shaping the intelligence behind tomorrow’s technology, this is your chance. This is more than just a gig—it’s a rare chance to help shape the future of AI from anywhere in the world, on your own terms. What You’ll Own: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. Labeling elements of a piece of content rather than the content as a whole. Assigning predefined categories or labels to items. Evaluating the perceived quality and/or appropriateness of content Generating labels to advance understanding of a concept, trend etc. Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images (rotation, flipping, cropping), generating new text (paraphrasing, summarization), or altering audio/video signals (speed modification, pitch shifting) to reduce overfitting and increase dataset diversity. Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. Ordering or ranking items based on a set of preferences or criteria. Creating prompts or questions that will be used to generate responses from a language model or other AI system. Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). Generating responses to prompts or questions using a language model or other AI system. Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. Producing concise summaries of longer pieces of text or data. Converting spoken language or audio content into written text. Converting text or spoken language from one language to another. Gathering and compiling various forms of data to be used for training, evaluating, or fine-tuning the AI models. This may include text, images, videos, audio files, or other types of digital content. You’ll Thrive in This Role If You Have: A Bachelor’s degree or higher in a humanities specialization is required. Advanced degrees are strongly preferred (Master’s or PhD) Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $15 p/hour, based on experience, skills, and qualifications. Please be aware of recruitment scams involving individuals or orga

Requirements

  • Must be eligible to work in one of: Remote - United States, United States
  • Fluent proficiency in English (Written & Verbal)
  • Reliable high-speed internet connection

Interview Prep

Sample questions for a Generative AI Associate role, written in-house to help you prepare.

How do you refine a prompt when a generated document is technically correct but not useful in its current form?

I isolate what's missing, whether it's structure, tone, or level of detail, rather than rewriting the whole prompt at once, since changing everything makes it hard to tell which adjustment fixed the problem. I test the revised prompt against more than one input before trusting the fix.

How do you evaluate whether an AI-generated spreadsheet or slide deck matches the format a professional in that field would produce?

I compare it against a real example of that document type I'd trust, checking structural conventions like section order and level of detail as well as factual accuracy. A document can be factually correct and still look nothing like what a practitioner would hand in.

What's your process for spotting subtle factual or logical errors in a long AI-generated document?

I check the numbers and claims that other parts of the document depend on first, since an error early in a chain of reasoning quietly propagates through everything downstream of it. I read dense, data-heavy sections more slowly than narrative ones, since that's where subtle errors tend to hide.

How do you decide how much editing versus full regeneration is the right fix for a flawed output?

If the structure is sound and only specific sections are wrong, I edit directly, since regenerating risks losing the parts that were already working. If the underlying approach is flawed throughout, I go back to the prompt instead of patching a document that's wrong at its foundation.

See all 10 questions for this role →

Why this role

This Generative AI Associate opening pays $15/hr and draws on Data Science knowledge you've already built. Onboarding covers the AI training process itself.

Talent pool

We're light on Data Science candidates

We've matched 9 people with a Data Science background against 293 Data Science listings we've tracked, so most go out without one. Set up a profile and we'll consider you for a role like this one.

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Common questions

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 asynchronous AI training work mean in practice?

No set hours, no check-ins, no meetings. You log in when you want, pick up an available task, complete it, and submit; nobody is waiting on you in real time. That's different from remote employment, where you're expected online during business hours. The tradeoff: you're competing with others for available tasks, so an empty queue means there's simply nothing to do until more work is released.

What does Data Science work look like for a Generative AI Associate?

Tasks here are scoped to Data Science, not generic labeling. As a Generative AI Associate, expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to Data Science) rather than following a one-size-fits-all rubric. If you don't have hands-on Data Science background, this is likely not the right listing to start with.

What specific skills does this listing call for?

Data Annotation, English, and Entry Level 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 much does this specific role pay?

This listing is posted at $15/hr, an hourly rate. Pay can change between when we last checked the listing and when you apply, so confirm the current number on the platform's own application page before committing time.

Can I apply from outside Remote - United States or the United States?

This specific role is open only to people based in Remote - United States and the United States. 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.