Generative AI Specialist - Red Team

Innodata Inc; Remote; CAD 80,000 - 100,000; Part time

Job summary

A data engineering company is seeking a Generative AI Specialist for a remote, part-time role. This position offers the opportunity to contribute to the development of generative AI while maintaining a flexible schedule. Candidates should have a humanities degree, with advanced English and bilingual French proficiency. Responsibilities include evaluating AI models, labeling content, and generating training data. The position is project-based, requiring engagement at up to 29 hours per week, with hourly pay starting at $25 CAD.

Qualifications

• Must have a Bachelor's degree or higher in a humanities specialization.
• Expert level proficiency (C1/C2) in English and Native/Bilingual proficiency in French.

Responsibilities

• Rate/assess the performance of AI models through evaluative questions.
• Labeling elements of content rather than the whole.
• Assign predefined categories to items.
• Evaluate the perceived quality of content.
• Generate labels to advance understanding of concepts.
• Create additional training data for models by modifying original data.
• Review data and identify product feature functionality.
• Label model outputs for identification purposes.
• Rank items based on preferences.
• Create prompts or questions for AI systems.
• Evaluate content relevance using a scale.
• Generate responses using language models.
• Rewrite existing text for clarity.
• Produce concise summaries of content.
• Compare content to drive determinations.
• Convert spoken language into written text.
• Translate text from one language to another.
• Gather various forms of data for training or evaluation.

Skills

Professional proficiency in English

Bilingual proficiency in French

Education

Bachelor’s degree in a humanities specialization

Master’s or PhD (preferred)

Job description

Job Title:

Generative AI Specialist - Humanities (English and French)

Location:

Fully Remote within Canada (excluding Quebec)

Employment Type:

Flexible Part-Time Role (part-time, up to 29 hrs weekly, no guaranteed hours. Project dependent.)

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 a 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.

It’s a rare chance to shape the future of AI from anywhere in the world, on your own terms.

What You’ll Be Doing:

• Evaluation: Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions.
• Annotation Labeling: Labeling elements of a piece of content rather than the content as a whole.
• Classification: Assigning predefined categories or labels to items.
• Content Quality: Evaluating the perceived quality and/or appropriateness of content.
• Content Understanding: Generating labels to advance understanding of a concept, trend etc.
• Data Augmentation: Creation of additional training data for machine learning models by applying transformations to the original data, such as modifying images, generating new text, or altering audio/video signals to reduce overfitting and increase dataset diversity.
• Grading: Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines.
• Identification Labeling: Labeling model outputs to identify if a piece of content is or isn’t something. Examples: identify clickbait; identifying gaming videos; identifying branded content.
• Preference Ranking: Ordering or ranking items based on a set of preferences or criteria.
• Prompt Generation: Creating prompts or questions that will be used to generate responses from a language model or other AI system.
• Relevance Evaluation: Projects that evaluate the relevance of content based on a relevancy scale (1‑3, 1‑5, etc.).
• Response Generation: Generating responses to prompts or questions using a language model or other AI system.
• Response Rewrite: Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines.
• Response Summarization: Producing concise summaries of longer pieces of text or data.
• Similarity Evaluation: Projects where content is compared in order to drive a determination.
• Transcription: Converting spoken language or audio content into written text.
• Translation: Converting text or spoken language from one language to another.
• 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 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 and Native/Bilingual proficiency in French.

Hourly Range:

$25.00 CAD

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.

We are an equal opportunity employer committed to fostering an inclusive, respectful, and diverse workplace. We welcome and encourage applications from individuals of all backgrounds and are dedicated to employment equity and building a team that reflects the diverse communities in which we live and operate.

In accordance with the Accessibility for Ontarians with Disabilities Act (AODA), we are committed to providing accommodations throughout the recruitment and selection process. If you require an accommodation, please let us know, and we will work with you to meet your needs.

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 FTC 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 [e-mail] and consider reporting it to the FTC at ReportFraud.ftc.gov.