AI Content Expert, Artificial General Intelligence

📍 Job Overview

Job Title: AI Content Expert, Artificial General Intelligence

Company: Jobs for Humanity

Location: Gdańsk, Pomeranian Voivodeship, Poland

Job Type: Contract

Category: AI & Machine Learning

Date Posted: August 21, 2025

Experience Level: Entry-level to Associate (0-2 years)

Remote Status: On-site

🚀 Role Summary

• Create and annotate high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content.
• Write grammatically correct texts in different styles with various degrees of creativity, strictly adhering to provided guidelines.
• Perform audits and quality checks of tasks completed by other specialists, if required.
• Make sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks.
• Dive deep into issues and implement solutions independently.
• Identify and report tooling bugs and suggest improvements.

📝 Enhancement Note: This role requires strong writing, research, and analytical skills, with a focus on creating high-quality training data for Large Language Models (LLMs). The role involves working closely with scientists and engineers to improve guidelines and tooling, indicating a collaborative and dynamic work environment.

📈 Primary Responsibilities

• Data Creation & Annotation: Create and annotate complex training data in multiple modalities, ensuring high quality and adherence to guidelines.
• Writing & Research: Write grammatically correct texts in different styles and conduct research to gather relevant information and understand complex topics.
• Quality Assurance: Perform audits and quality checks of tasks completed by other specialists, if required.
• Problem Solving: Make sound judgments and logical decisions when faced with ambiguous or incomplete information, and dive deep into issues to implement solutions independently.
• Tooling Improvement: Identify and report tooling bugs and suggest improvements to enhance the data creation process.

🎓 Skills & Qualifications

Education: High-school diploma or equivalent.

Experience: Entry-level to Associate (0-2 years) with proven experience working with written language data, including experience with annotation and other forms of data markup.

Required Skills:

• Strong proficiency in English (C1 level in CEFR scale)
• Excellent writing, reading, and comprehension skills
• Strong research skills and understanding of basic academic integrity
• Excellent attention to detail and ability to focus for extended periods
• Comfortable with high-school level STEM subjects
• Ability to write and evaluate diverse subject matter across various domains
• Ability to adapt writing style to suit various style guidelines and customers
• Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy

Preferred Skills:

• Bachelor’s degree in a relevant field or equivalent professional experience
• Experience with creating complex data for LLM training and evaluation
• Proven experience working with command line interfaces and basic UNIX commands
• Familiarity with common markup languages such as HTML, XML, Markdown
• Familiarity with common standard text formats such as JSON, CSV, RTF
• Working knowledge of Python or another scripting language
• Familiarity with regular expressions syntax
• Familiarity with Large Language Models
• Comfort in annotation work that may include sensitive content

📝 Enhancement Note: While a bachelor’s degree is preferred, the company is open to considering candidates with equivalent professional experience. Familiarity with Large Language Models and experience creating complex data for LLM training and evaluation would be particularly valuable for this role.

📊 Campaign Portfolio & Results Requirements

Portfolio Essentials:

• Examples of complex training data created and annotated in multiple modalities (text, image, video)
• Writing samples demonstrating adaptability to different styles and guidelines
• Evidence of problem-solving skills and independent decision-making in ambiguous situations
• Documentation of tooling bugs identified and improvements suggested

Campaign Documentation:

• Detailed notes on research conducted and sources used for creating training data
• Records of quality checks performed and any feedback received
• Documentation of guidelines reviewed and updated, in collaboration with scientists and engineers
• Records of tooling bugs reported and improvements implemented

💵 Compensation & Benefits

Salary Range: Not specified. According to Glassdoor, the average salary for an AI Content Specialist in Poland is around 7,000 PLN (approximately 1,500 EUR) per month. However, this role may offer a higher salary given the required skills and experience.

Benefits:

• Fixed-term contract
• Diverse team with regular meetings, training, and Amazon events throughout the year
• Equal opportunities employer with a focus on inclusive culture and workplace accommodation for individuals with disabilities

Working Hours: 40 hours per week, Monday through Friday, with an eight-hour shift.

📝 Enhancement Note: While the salary range is not specified, the average salary for an AI Content Specialist in Poland can be used as a benchmark. The company offers a fixed-term contract with a diverse team and inclusive culture, indicating a supportive work environment.

🎯 Team & Company Context

🏢 Company Culture

Industry: Artificial Intelligence & Machine Learning

Company Size: Not specified. However, the mention of a “Data Team” and regular Amazon events suggests a mid-to-large-sized company with a structured team organization.

Founded: Not specified. The company is likely established, given the mention of regular Amazon events and an inclusive culture.

Team Structure:

• The AI Content Expert will work within the Data Team, collaborating with scientists and engineers to improve guidelines and tooling.
• The team works strictly in the office Monday through Friday with an eight-hour shift, indicating a structured and collaborative work environment.

Methodology:

• The AI Content Expert will create and annotate complex training data in multiple modalities, following provided guidelines and collaborating with team members to improve the data creation process.
• The team is constantly looking for ways to improve their capabilities and deliver the best product possible, indicating a focus on continuous improvement and innovation.

Company Website: jobsforhumanity.com

📝 Enhancement Note: While the company size and founding date are not specified, the mention of a Data Team and regular Amazon events suggests a mid-to-large-sized company with a structured team organization and established culture. The team’s focus on continuous improvement and innovation indicates a dynamic and collaborative work environment.

📈 Career & Growth Analysis

Marketing Career Level: Not applicable, as this role is focused on AI content creation and data analysis rather than marketing.

Reporting Structure: The AI Content Expert will report to the Data Team, collaborating with scientists and engineers to improve guidelines and tooling.

Marketing Impact: Not applicable, as this role is focused on AI content creation and data analysis rather than marketing.

Growth Opportunities:

• Opportunities for professional development and training within the Data Team.
• Potential to work on diverse and complex projects, contributing to the improvement of Large Language Models (LLMs) capabilities.
• Exposure to a dynamic and collaborative work environment, fostering personal and professional growth.

📝 Enhancement Note: While this role is not focused on marketing, it offers opportunities for professional development and growth within the AI and Machine Learning field. The collaborative and dynamic work environment can contribute to the personal and professional growth of the AI Content Expert.

🌐 Work Environment

Office Type: On-site, with a structured eight-hour shift Monday through Friday.

Office Location(s): Gdańsk, Pomeranian Voivodeship, Poland

Workspace Context:

• The AI Content Expert will work within the Data Team, collaborating with scientists and engineers to improve guidelines and tooling.
• The team is diverse, with regular meetings, training, and Amazon events throughout the year, fostering a collaborative and inclusive work environment.
• The company offers workplace accommodation for individuals with disabilities, indicating a focus on accessibility and inclusivity.

Work Schedule: 40 hours per week, Monday through Friday, with an eight-hour shift.

📝 Enhancement Note: The on-site work environment offers a structured and collaborative workspace, with a diverse team and regular events fostering a collaborative and inclusive culture. The company’s focus on accessibility and inclusivity indicates a supportive work environment for all employees.

📄 Application & Portfolio Review Process

Interview Process:

• Application Review: Submit your application through the application link, highlighting your relevant experience and skills.
• Phone/Video Screen: A brief phone or video call to discuss your qualifications and experience.
• On-site Interview: An on-site interview with the Data Team to discuss your portfolio, problem-solving skills, and cultural fit.
• Final Evaluation: A final evaluation based on your interview performance, portfolio, and problem-solving skills.

Portfolio Review Tips:

• Highlight your experience with written language data, annotation, and other forms of data markup.
• Include examples of complex training data created and annotated in multiple modalities (text, image, video).
• Demonstrate your ability to write in different styles and adapt to various guidelines and customers.
• Showcase your problem-solving skills and independent decision-making in ambiguous situations.
• Document your research process, quality checks, and tooling improvements.

Challenge Preparation:

• Familiarize yourself with the company’s focus on AI and Machine Learning, and be prepared to discuss your experience and skills in this area.
• Brush up on your English language skills, as strong proficiency is required for this role.
• Prepare examples of your writing and annotation work, demonstrating your ability to create high-quality training data.

ATS Keywords: (Organized by category)

• AI & Machine Learning: Large Language Models, LLM, Data Analysis, Content Generation, Annotation, Training Data, Complex Data, Technical Content, Science-related Content, Multimodal Data
• Writing & Research: Writing, Research, Grammar, Style, Creativity, Guidelines, Academic Integrity, Plagiarism, Attention to Detail, Focus, STEM Knowledge, Adaptability, Quality Assurance, Problem Solving, Tool Improvement, Language Proficiency
• Tools & Technologies: Command Line Interfaces, UNIX Commands, Markup Languages (HTML, XML, Markdown), Standard Text Formats (JSON, CSV, RTF), Python, Scripting Languages, Regular Expressions, Large Language Models

📝 Enhancement Note: The application and portfolio review process is designed to assess the candidate’s experience with written language data, annotation, and other forms of data markup, as well as their problem-solving skills and cultural fit. The provided ATS keywords can help candidates tailor their resumes and portfolios to highlight relevant skills and experience.

🛠 Tools & Technology Stack

Primary Tools:

• Command Line Interfaces (CLI) and basic UNIX commands for tooling improvement and data manipulation.
• Markup languages such as HTML, XML, Markdown for data annotation and structuring.
• Standard text formats such as JSON, CSV, RTF for data exchange and storage.
• Python or another scripting language for data analysis, manipulation, and automation.

Analytics & Attribution:

• Not specified. However, the role may involve using analytics tools to evaluate the quality and effectiveness of the training data created.

Campaign Management & Automation:

• Not specified. However, the role may involve using campaign management tools to track and optimize the data creation process.

📝 Enhancement Note: The primary tools for this role are focused on data analysis, manipulation, and automation. While the role may involve using analytics and campaign management tools, the focus is primarily on creating and annotating high-quality complex training data.

👥 Team Culture & Values

Marketing Values: Not applicable, as this role is focused on AI content creation and data analysis rather than marketing.

Collaboration Style:

• The AI Content Expert will collaborate with scientists and engineers within the Data Team to improve guidelines and tooling.
• The team is diverse, with regular meetings, training, and Amazon events throughout the year, fostering a collaborative and inclusive work environment.
• The company offers workplace accommodation for individuals with disabilities, indicating a focus on accessibility and inclusivity.

📝 Enhancement Note: While this role is not focused on marketing, the collaborative and inclusive work environment fosters a supportive and engaging culture for all employees.

⚡ Challenges & Growth Opportunities

Challenges:

• Creating and annotating complex training data in multiple modalities, adhering to strict guidelines.
• Making sound judgments and logical decisions when faced with ambiguous or incomplete information.
• Identifying and reporting tooling bugs and suggesting improvements.
• Adapting to fast-paced environments with changing circumstances, direction, and strategy.

Learning & Development Opportunities:

• Opportunities for professional development and training within the Data Team.
• Potential to work on diverse and complex projects, contributing to the improvement of Large Language Models (LLMs) capabilities.
• Exposure to a dynamic and collaborative work environment, fostering personal and professional growth.

📝 Enhancement Note: The challenges and growth opportunities for this role are centered around creating high-quality complex training data, collaborating with team members, and adapting to a fast-paced environment. The learning and development opportunities focus on professional growth within the AI and Machine Learning field.

💡 Interview Preparation

Strategy Questions:

• Data Creation & Annotation: Discuss your experience creating and annotating complex training data in multiple modalities, adhering to strict guidelines.
• Writing & Research: Describe your ability to write in different styles and adapt to various guidelines and customers, as well as your research skills and understanding of academic integrity.
• Problem Solving: Provide examples of your problem-solving skills and independent decision-making in ambiguous situations.
• Tooling Improvement: Explain your experience identifying and reporting tooling bugs and suggesting improvements.

Company & Culture Questions:

• Discuss your familiarity with the company’s focus on AI and Machine Learning, and how your experience and skills align with the role’s requirements.
• Describe your preferred work environment and how you adapt to fast-paced environments with changing circumstances, direction, and strategy.

Portfolio Presentation Strategy:

• Highlight your experience with written language data, annotation, and other forms of data markup.
• Include examples of complex training data created and annotated in multiple modalities (text, image, video).
• Demonstrate your ability to write in different styles and adapt to various guidelines and customers.
• Showcase your problem-solving skills and independent decision-making in ambiguous situations.
• Document your research process, quality checks, and tooling improvements.

📝 Enhancement Note: The interview preparation strategy focuses on the candidate’s experience with data creation, annotation, and problem-solving, as well as their ability to adapt to a fast-paced environment and collaborate with team members. The company and culture questions aim to assess the candidate’s fit within the organization and their understanding of the role’s requirements.

📌 Application Steps

To apply for this AI Content Expert position:

• Submit your application through the application link, highlighting your relevant experience and skills.
• Prepare for a brief phone or video screen to discuss your qualifications and experience.
• Prepare for an on-site interview with the Data Team, focusing on your portfolio, problem-solving skills, and cultural fit.
• Prepare for a final evaluation based on your interview performance, portfolio, and problem-solving skills.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and marketing industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.