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SME

ClickUp Specialist

SMEBusiness and Consulting

Up to $25/hr

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In this hourly, remote contractor role, you will work as a ClickUp Specialist (SME) to create realistic, challenging computer-based tasks using ClickUp and related project-management workflows. You will design practical ClickUp tasks, document them clearly in SuperAnnotate, ensure your setup supports the task, and record yourself executing the task on your computer. Tasks may include creating workspaces, spaces, folders, lists, tasks, subtasks, statuses, custom fields, dashboards, automations, docs, comments, views, assignments, deadlines, or project-tracking workflows. Your work will help train advanced AI models to better understand how real users organize and manage work in project-management tools. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your ClickUp expertise directly helps improve the world’s premier AI models by teaching them how real users complete practical project-management, admin, operations, and team-collaboration workflows. Requirements - Hands-on experience using ClickUp for task management, project tracking, dashboards, docs, automations, team collaboration, or operations workflows. - English proficiency at B2 level or higher to understand project instructions, document tasks clearly, and communicate with the project team. - Comfortable using a computer, browser-based tools, workspaces, files, permissions, and recording workflows. - Ability to come up with realistic and challenging ClickUp tasks that reflect actual admin, operations, project management, sales, marketing, support, HR, or team-collaboration use cases. - Strong understanding of ClickUp basics such as workspaces, spaces, folders, lists, tasks, statuses, assignees, due dates, custom fields, views, dashboards, docs, and automations. - Ability to ensure your setup supports the task, including having ClickUp access, sample workspace data, tasks/projects prepared, and any required references ready before recording. - High attention to detail when preparing the task, executing the workflow, and checking that the recording is complete and understandable. - Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones. - Additional professional skills are appreciated, including project management, admin, operations, sales, marketing, HR, customer support, documentation, or other computer-based workflows. Responsibilities - Create realistic ClickUp tasks: Come up with realistic and challenging tasks that can be executed on the computer using ClickUp, then document the task clearly in SuperAnnotate. - Prepare the work environment: Ensure your setup supports the task, including having ClickUp access, workspace/projects prepared, sample tasks available, permissions ready, and references prepared before recording. - Record task execution: Record yourself executing the ClickUp task on your computer while following project instructions and ensuring the workflow is clear, complete, and realistic. - Document task context: Provide enough task context, steps, goals, workspace/project details, and notes so reviewers can understand what the task is and how it was completed. - Demonstrate practical software use: Complete workflows involving task creation, custom fields, views, dashboards, docs, statuses, assignments, deadlines, automations, or project updates where relevant. - Maintain submission quality: Review your recording and documentation before submission to ensure the task is complete, understandable, realistic, and aligned with project guidelines. Skills - Project Management - Automations - Admin - Dashboards - Screen Recording - Computer Use - ClickUp - English - Task Management - Workflows Additional skills - ClickUp - Task Management - Project Tracking - Workflow Automation - ClickUp Dashboards - ClickUp Docs - ClickUp Views - Custom Fields - Spaces & Folders - List Management - Status Workflows - Permissions Management - Workspace Administration - Team Collaboration - Process Documentation - Workflow Recording - Operations Management - Project Management - Agile Methodologies - Kanban - SOP Development - Business Process Improvement - Remote Work - Time Management - Attention to Detail - Stakeholder Communication - English (B2+) - CRM Workflows - Marketing Operations - Customer Support Operations

In this hourly, remote contractor role, you will work as an Anthropology Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across anthropology-focused AI training projects. You will review AI-generated anthropology content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for anthropological accuracy, cultural context, theory application, ethnographic sensitivity, methodological rigor, ethical awareness, bias sensitivity, terminology quality, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong anthropology expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your anthropology quality leadership will directly help improve the world’s premier AI models by ensuring that anthropology training data is accurate, culturally sensitive, ethically aware, research-informed, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network. Requirements - Bachelor’s, Master’s, or PhD degree in Anthropology, Cultural Anthropology, Archaeology, Biological Anthropology, Linguistic Anthropology, Sociology, Area Studies, Museum Studies, or a closely related field. - Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback. - 3+ years of experience in anthropology research, teaching, ethnography, archaeology, museum/heritage work, cultural analysis, academic writing, fieldwork, or related workflows. - Strong understanding of anthropological theory, cultural relativism, ethnographic methods, kinship, ritual, language/culture relationships, material culture, human evolution, archaeology, ethics, and representation. - Ability to evaluate anthropology content against detailed rubrics and identify issues such as cultural stereotyping, ethnocentrism, unsupported generalizations, outdated terminology, methodological errors, weak contextualization, or ethically problematic framing. - Familiarity with areas such as ethnography, participant observation, archaeological methods, human origins, kinship systems, religion/ritual, migration, colonialism, Indigenous studies, museum ethics, or linguistic anthropology is preferred. - Experience leading or supporting remote teams of researchers, educators, reviewers, fieldworkers, annotators, or QAs is strongly preferred. - Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. - Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation. - Experience with AI training, data annotation, LLM evaluation, social science QA, academic review, cultural sensitivity review, or rubric-based review is a strong plus. Responsibilities - Quality monitoring: Spot-check anthropology items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. - Anthropology review: Evaluate AI-generated anthropology explanations, ethnographic summaries, cultural comparisons, archaeology discussions, human evolution explanations, and social/cultural reasoning for accuracy and sensitivity. - Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and anthropology-specific review standards. - Question handling: Respond to trainer/QA questions clearly and promptly, especially around cultural context, anthropological concepts, ethnographic methods, archaeology, human evolution, ethics, representation, and rubric interpretation. - Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed. - Documentation: Create and maintain anthropology project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials. - Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and anthropology-specific review requirements. - Quality alignment: Ensure all trainers and QAs apply anthropology review guidelines consistently and understand updates as projects evolve. - Bias and ethics review: Flag ethnocentric, stereotyping, culturally insensitive, outdated, unsupported, or ethically problematic anthropology content. - Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for anthropology AI training projects. Skills - Research Methods - LLM Evaluation - Archaeology - Anthropology - AI Training - Trainer Feedback - Human Evolution - Cultural Anthropology - Ethnography - Culture Additional skills - Quality Assurance - Rubric-Based Evaluation - Content Review - Cultural Sensitivity Review - Cultural Relativism - Anthropological Theory - Ethnographic Methods - Participant Observation - Fieldwork - Cultural Analysis - Academic Writing - Research Methodology - Qualitative Research - Archaeological Methods - Material Culture Studies - Museum Studies - Museum Ethics - Heritage Management - Indigenous Studies - Linguistic Anthropology - Kinship Studies - Religion and Ritual Studies - Migration Studies - Colonialism/Postcolonial Studies - Ethics in Research - Bias Detection - Terminology Standardization - Style Guide Development - AI Data Annotation - LLM Evaluation

SME

Estonian Team Lead

SMELanguages / Business and Consulting

Up to $40/hr

Estonia

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In this hourly, remote contractor role, you will work as an Estonian Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Estonian AI training projects. You will review AI-generated Estonian content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for accuracy, fluency, grammar, spelling, tone, cultural appropriateness, meaning preservation, instruction-following, formatting, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong Estonian and English skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote teams. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Estonian quality leadership will directly help improve the world’s premier AI models by ensuring that Estonian training data is natural, accurate, culturally appropriate, well-documented, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Requirements - Bachelor’s or Master’s degree in Estonian, Linguistics, Translation, Communications, Journalism, English, Education, Quality Assurance, or a relevant domain/related field. - Native or near-native Estonian proficiency with strong reading and writing skills. - Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear feedback in English. - 3+ years of professional experience in Estonian writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows. - Strong understanding of Estonian grammar, spelling conventions, punctuation, diacritics, case endings, compounds, word order, tone, register, and cultural context. - Ability to evaluate Estonian content against detailed rubrics and identify issues such as mistranslation, literal phrasing, unnatural tone, incorrect case usage, missing diacritics, hallucinated claims, ambiguity, or inconsistent terminology. - Experience leading or supporting remote teams of trainers, annotators, reviewers, editors, or QAs is strongly preferred. - Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. - Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, and other quality documentation. - Experience with AI training, data annotation, large language models, prompt/response evaluation, or rubric-based LLM QA is a strong plus. Responsibilities - Quality monitoring: Spot-check Estonian items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. - Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, and quality expectations. - Question handling: Respond to trainer/QA questions clearly and promptly, especially around Estonian wording, grammar, case endings, compounds, register, translation fidelity, cultural context, terminology, and edge cases. - Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed. - Documentation: Create and maintain Estonian project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, and onboarding materials. - Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and Estonian-specific style requirements. - Quality alignment: Ensure all trainers and QAs apply Estonian language guidelines consistently and understand updates as projects evolve. - Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for Estonian-language projects. Skills - LLM Evaluation - Translation Quality Review - Estonian - Style Guides - AI Training - Documentation - Trainer Feedback - English - Estonian Quality Assurance - Localization QA Additional skills - Estonian - English - Quality Assurance (QA) - Linguistic QA - Localization - Translation - Editing - Proofreading - Estonian Grammar - Terminology Management - Style Guides - Content Review - Copyediting - Error Taxonomy - Rubric-Based Evaluation - Data Annotation - AI Training - LLM Evaluation - Prompt Evaluation - Fact-Checking - Consistency Checks - Cultural Localization - Reviewer Training - Team Leadership - Remote Collaboration - Google Sheets - Google Docs - Discord - Jira - Quality Documentation

SME

Financial Analyst

SMEFinance / Business and Consulting / Software, AI and Data

SMELanguages / Business and Consulting

Up to $36/hr

Greece

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In this hourly, remote contractor role, you will work as a Greek Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Greek AI training projects. You will review AI-generated Greek content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for accuracy, fluency, grammar, spelling, tone, cultural appropriateness, meaning preservation, instruction-following, formatting, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong Greek and English skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote teams. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Greek quality leadership will directly help improve the world’s premier AI models by ensuring that Greek training data is natural, accurate, culturally appropriate, well-documented, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Requirements - Bachelor’s or Master’s degree in Greek, Linguistics, Translation, Communications, Journalism, English, Education, Quality Assurance, or a relevant domain/related field. - Native or near-native Greek proficiency with strong reading and writing skills. - Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear feedback in English. - 3+ years of professional experience in Greek writing, editing, translation, localization, content QA, AI training, education, annotation, or related language-review workflows. - Strong understanding of Greek grammar, spelling conventions, punctuation, tone, register, modern Greek usage, and cultural context. - Comfortable handling regional/audience variation where relevant, including Greece vs Cyprus usage and formal vs conversational tone. - Ability to evaluate Greek content against detailed rubrics and identify issues such as mistranslation, literal phrasing, unnatural tone, hallucinated claims, ambiguity, incorrect register, or inconsistent terminology. - Experience leading or supporting remote teams of trainers, annotators, reviewers, editors, or QAs is strongly preferred. - Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. - Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, and other quality documentation. - Experience with AI training, data annotation, large language models, prompt/response evaluation, or rubric-based LLM QA is a strong plus. Responsibilities - Quality monitoring: Spot-check Greek items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. - Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, and quality expectations. - Question handling: Respond to trainer/QA questions clearly and promptly, especially around Greek wording, grammar, register, translation fidelity, cultural context, Greece vs Cyprus usage, and edge cases. - Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed. - Documentation: Create and maintain Greek project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, and onboarding materials. - Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and Greek-specific style requirements. - Quality alignment: Ensure all trainers and QAs apply Greek language guidelines consistently and understand updates as projects evolve. - Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for Greek-language projects. Skills - Greek Quality Assurance - LLM Evaluation - Translation Quality Review - Style Guides - AI Training - Documentation - Trainer Feedback - Greek - English - Localization QA Additional skills - Greek (Modern) - English Proficiency - Localization - Translation - Editing - Proofreading - Linguistic QA - Content Quality Assurance (QA) - Quality Management - Rubric-Based Evaluation - Terminology Management - Style Guides - Greek Grammar - Greek Orthography - Punctuation - Tone & Register - Cultural Adaptation - Greece vs Cyprus Language Variants - Transcreation - Fact-Checking - Error Taxonomy - AI Training Data - Data Annotation - LLM Evaluation - Prompt Evaluation - Remote Team Leadership - Reviewer/Annotator Training - Google Sheets - Google Docs - Discord

SME

R Team Lead

SMESoftware, AI and Data / STEM

Up to $65/hr

United States

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In this hourly, remote contractor role, you will work as an R Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across R programming and data-analysis AI training projects. You will review AI-generated R code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected standards. You will assess work for code correctness, statistical validity, data reasoning, package usage, reproducibility, debugging accuracy, readability, visualization quality, formatting, instruction-following, and rubric adherence. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your R quality leadership will help ensure R training data is accurate, reproducible, statistically sound, clearly explained, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network. Requirements - Bachelor’s or Master’s degree in Statistics, Data Science, Mathematics, Computer Science, Economics, Biology, Social Sciences, or related quantitative field. - Strong grasp of English to follow guidelines and provide clear feedback. - 3+ years of experience using R for data analysis, statistics, research, analytics, teaching, coding, or technical review. - Strong understanding of R syntax, data frames, vectors, functions, lists, factors, missing data, tidyverse, base R, statistical modeling, and visualization. - Ability to identify issues such as incorrect statistical assumptions, invalid package usage, non-reproducible code, data leakage, flawed transformations, hallucinated functions, or misleading charts. - Familiarity with dplyr, tidyr, ggplot2, readr, stringr, purrr, data.table, Shiny, R Markdown/Quarto, caret/tidymodels, lme4, survival, Git, and reproducible workflows is preferred. - Experience leading remote teams of trainers, analysts, reviewers, educators, or QAs is strongly preferred. - Comfortable with Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and PM systems. - Highly organized and able to maintain style guides, trackers, FAQs, honeypots, calibration tasks, and onboarding materials. - Experience with AI training, data annotation, LLM evaluation, code QA, or rubric-based review is a strong plus. Responsibilities - Spot-check R programming and data-analysis items. - Review AI-generated R code, statistical explanations, visualizations, data-wrangling steps, and modeling workflows. - Communicate project updates and R-specific standards on Discord. - Answer trainer/QA questions around R syntax, packages, statistical reasoning, reproducibility, plots, and rubric interpretation. - DM inactive contributors and manage activation tracking. - Create and maintain R documentation, style guides, examples, trackers, FAQs, honeypots, and onboarding materials. - Run onboarding/training calls for R contributors. - Flag misleading statistical claims, invalid methods, non-reproducible workflows, or hallucinated packages/functions. - Improve QA processes based on recurring gaps. Skills - Statistics - LLM Evaluation - Code Review - R QA - Data Analysis - Visualization - R - AI Training - Trainer Feedback - tidyverse Additional skills - R - Tidyverse - Base R - Data Analysis - Statistical Modeling - Data Visualization - dplyr - tidyr - ggplot2 - readr - stringr - purrr - data.table - Shiny - R Markdown - Quarto - tidymodels - caret - lme4 - survival - Reproducible Research - Git - GitHub - Code Review - Technical Writing - Quality Assurance (QA) - Team Leadership - Remote Team Management - LLM Evaluation - Data Annotation

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