Generative AI Specialist – Humanities SME

Job Title: Generative AI Specialist – Humanities SME

Location: Fully Remote within the U.S. (excluding Alaska, California, Colorado, Nevada, Puerto Rico or Nebraska)

Employment Type: Flexible Part-Time Role (part-time, up to 25 hours weekly, no hours guaranteed)

Who we are: 

Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider-of-choice for 4 out of 5 of the world’s biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine. 

By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we’re helping usher in the promise of AI. Innodata offers a powerful combination of both digital data solutions and easy-to-use, high-quality platforms. 

Our global workforce includes over 7,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We’re poised for a period of explosive growth over the next few years. 

About 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 Specialists 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 your field 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 your field 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 Be Doing:

Core tasks would include (any/multiple of) but not limited to the following:  

1. Evaluation: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions.  

1. Annotation Labeling: Labeling elements of a piece of content rather than the content.  

1. Classification: Assigning predefined categories or labels to items.  

1. Content Quality: Evaluating the perceived quality and/or appropriateness of content  

1. Content Understanding: Generating labels to advance understanding of a concept, trend etc.  

1. Data Augmentation: 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.  

1. Grading: Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines.  

1. Identification Labeling: Labeling model outputs to identify if a piece of content is or isn't something. Examples: identifying clickbait; identifying gaming videos; identifying branded content. 

1. Preference Ranking: Ordering or ranking items based on a set of preferences or criteria.  

1. Prompt Generation: Creating prompts or questions that will be used to generate responses from a language model or other AI system.  

1. Relevance Evaluation: Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.).  

1. Response Generation: Generating responses to prompts or questions using a language model or other AI system.  

1. Response Rewrite: Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines.  

1. Response Summarization: Producing concise summaries of longer pieces of text or data.  

1. Similarity Evaluation: Projects where content is compared in order to drive a determination.  

1. Data Collection: 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. 

Minimum Qualifications: 

• A Doctorate degree is required; fourth year Doctorate Students can be considered on a case-by-case basis scenario.

• Subject Mater Expertise in fields such as: Linguistics, Mathematics, Physics, Computer Science, Chemistry, Applied Mathematics, Electrical Engineering, Biology, Medicine, Genetics, History, Economics, Ecology, Artificial Intelligence, Musicology, Philosophy, Neuroscience, Law, Art History, Biochemistry, Astronomy, Classics, Chess, Chemical Engineering, Microbiology, Classical Ballet, Materials Science, Poetry, Quantum Mechanics, Aerospace Engineering, Civil Engineering, Mechanical Engineering, Geography, Robotics, Data Science, Molecular Biology, Statistics, Immunology, Education, Logic, Computational Biology, Psychology, English Literature, Machine Learning, Puzzle, Cultural Studies, Marine Biology, Archaeology, and Biophysics

• Hourly Range: $30.00 USD

  • Hourly rates at Innodata vary depending on a wide array of factors, which may include but are not limited to the role, skill set, educational background and geographic location. 

Salary : $30