Role Description 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. Qualifications - 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. Requirements - The expected hourly salary range for this position is $15 p/hour, based on experience, skills, and qualifications. Important Notice Please be aware of recruitment scams involving individuals or organizations falsely claiming to represent employers. Innodata will never ask for payment, banking details, or sensitive personal information during the application process. To learn more on how to recognize job scams, please visit the Federal Trade Commission’s guide at https://consumer.ftc.gov/articles/job-scams . If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

• Define the ICP wedge (creators vs. teams vs. agencies), pricing model, and product positioning • Expand from internal design partners to external users (creators, teams, agencies), validate retention and willingness to pay, and build the go-to-market motion through creator-led distribution • Partner with the FutureSight product and engineering team to ship V1 and iterate on user feedback, with a focus on extraction quality, clustering relevance, and draft usefulness • Lead the seed raise, supported by FutureSight's network and traction • Recruit and lead the founding team, and establish the cultural foundation of the company

• Define the ICP wedge (creators vs. teams vs. agencies), pricing model, and product positioning • Expand from internal design partners to external users (creators, teams, agencies), validate retention and willingness to pay, and build the go-to-market motion through creator-led distribution • Partner with the FutureSight product and engineering team to ship V1 and iterate on user feedback, with a focus on extraction quality, clustering relevance, and draft usefulness • Lead the seed raise, supported by FutureSight's network and traction • Recruit and lead the founding team, and establish the cultural foundation of the company

• Define the ICP wedge (creators vs. teams vs. agencies), pricing model, and product positioning • Expand from internal design partners to external users (creators, teams, agencies), validate retention and willingness to pay, and build the go-to-market motion through creator-led distribution • Partner with the FutureSight product and engineering team to ship V1 and iterate on user feedback, with a focus on extraction quality, clustering relevance, and draft usefulness • Lead the seed raise, supported by FutureSight's network and traction • Recruit and lead the founding team, and establish the cultural foundation of the company