Generative AI Specialist Humanities (English and Swedish)

Job description

Job Title: Generative AI Specialist - Humanities (English and Swedish)

Location: Fully Remote within the U.S. (excluding California Washington Alaska Colorado Montana New York Puerto Rico Nevada Nebraska)

Employment Type: Full-Time (40 hours per week) Fixed Term (3-5 weeks with potential Extension)

Who we are:

Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2000 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 worlds 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 were 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 7000 employees in the United States Canada United Kingdom the Philippines India Sri Lanka Israel and Germany. Were poised for a period of explosive growth over the next few years.

About the Role:

At Innodata were partnering with the worlds leading technology companies to build the future of generative AI and large language models (LLMs). Were 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. Its a part-time remote flexible project-specific opportunity designed for those who want to make a real impacton their schedule. Whether youre 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.

Youll be helping LLMs learn the intricacies of language and reasoningnot just how to write but how to think. If youve ever dreamed of shaping the intelligence behind tomorrows technology this is your chance.

This is more than just a gigits a rare chance to help shape the future of AI from anywhere in the world on your own terms.

What Youll 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 as a whole.

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 projects guidelines.

1. Identification Labeling: Labeling model outputs to identify if a piece of content is or isnt something. Examples: identify 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. Transcription: Converting spoken language or audio content into written text.

1. Translation: Converting text or spoken language from one language to another.

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.

Job requirements

Minimum Qualifications:

• A Bachelors degree or higher in a humanities specialization is required. Advanced degrees are strongly preferred (Masters or PhD)

• Professional or Expert level proficiency (C1/C2) in English and Swedish

Hourly Range: $25.00USD

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.

Innodata is an equal opportunity employer and values diversity. We do not discriminate on the basis of race religion color national origin gender gender identity or expression sexual orientation age marital status veteran status disability status or any other legally protected status.

Innodata is committed to creating an inclusive environment for all employees and applicants. If you need assistance or accommodation during the application or recruitment process due to a disability please contact us and we will be happy to assist.

Applicants must be legally authorized to work in the United States at the time of hire. Innodata is unable to provide visa sponsorship now or in the future for this position.

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 Commissions guide at

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