Innodata Inc

Role Description In this position, you’ll manage the overall performance and governance of the Statement of Work (SOW), manage the day-to-day operations in accordance with the requirements of the Service Level Agreements (SLAs) set out in the SOW, promptly identify and resolve Service delivery issues including implementation of preventive measures, handle transition management during set-up phase or expansion phase. As a key player in the Operations teams, you’ll support the deployment of infrastructure necessary to perform the Services, including all technology, financial, human resources, security, facilities, and communication resources. Install all Service delivery processes and Service level reporting mechanisms. As a key leader, you’re to provide exceptional people management, mentorship, and career development to members, including your managers and agents/raters, achieve low attrition levels and high employee engagement. Drive Operations teams to deliver continuous improvement and productivity gains. Flag and escalate business risks to both internal and external stakeholders, keeping in mind the internal strategies to support Innodata overall Project Delivery goals and objectives. What You’ll Own - Leading end-to-end small to medium project deployment in collaboration with the Total Quality Management (TQM) teams and all stakeholders. - Providing thought leadership in resolving language and dialect nuances to advance recruitment, evaluation of applicants and performance evaluation of personnel under specific languages of expertise. - Supporting total customer satisfaction. - Supporting all strategies, processes and initiatives of TQM teams and promote collaboration of all Operations leaders as needed and in improving Client’s community and support experience. - Playing an active role in improving policies, products, process and support system processes by providing insights and offering suggestions including feedback from the teams. - Identifying potential risks or issues with project implementations and proactively drive communications with internal and external stakeholders. - Translating business requirements into operations plans. - Crafting and implementing tracking, monitoring, and reporting methodologies of all SLAs required per SOW. - Ensuring achievement of KPIs, directing Root Cause Analyses documentation among team members, and defining resolution and operations strategies to achieve all SLAs. - Assessing and prioritizing the top-operations issues affecting the team. - Collaborating with all support teams, implement project and process kick-offs, monitor and report project/process/initiative status, initiate resolution discussions for any challenges. - Managing, monitoring, and communicating change delivery items as needed. - Overseeing new hire deployment status to client platforms and knowledge of SLAs. - Coordinating mutual goals with TQM teams. - Initiating productivity, process, security, and facilities improvement plans. - Partnering with TQM teams to ensure alignment. - Coaching and mentoring all leaders within your span including how they should drill down on the same people management strategies to agents. - Bolstering the management of training programs including planning, design, development, implementation, delivery, process review and performance evaluation. - Supporting management on business and expansion strategies, revenue and profitability goals, and overall financial improvement plans. Qualifications - Experience and passion for managing large diverse teams of experts across multiple sites in a fast-paced environment, able to deal with rapid change and ambiguity. - Strategic thinker with strong analytical and problem-solving skills. - 5+ years of experience in operations and people management experience, including managing leaders, and a strong desire to develop team members. - Excited to be part of a global operations team, design effective business operations, tackle complex problems, and develop individual team members. - Proven ability to manage multiple projects concurrently through to successful implementation in an operational environment. - Adaptable and energized by a fast-paced environment. - Possesses creative energy, drive, initiative, commitment, and enthusiasm. - Exceptional candidate with bachelor’s degree or equivalent required. Certification on Project Management or Six Sigma a plus. - Excellent communication skills, written and oral. Important Notice 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 Commission’s 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 verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Role Description 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 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. 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 Own - Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Labeling elements of a piece of content rather than the content as a whole. - Assigning predefined categories or labels to items. - Evaluating the perceived quality and/or appropriateness of content. - Generating labels to advance understanding of a concept, trend, etc. - 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. - Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. - Ordering or ranking items based on a set of preferences or criteria. - Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). - Generating responses to prompts or questions using a language model or other AI system. - Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. - Producing concise summaries of longer pieces of text or data. - Converting spoken language or audio content into written text. - Converting text or spoken language from one language to another. - 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. 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. Requirements - The expected hourly salary range for this position is $21 CAD p/hour, based on experience, skills, and qualifications. Company Description Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.

Role Description We are building an industry-leading Agentic Observability Platform to help enterprises evaluate, monitor, and improve AI agents throughout their lifecycle. This is not a traditional product marketing role. You will help build the business from the ground up alongside Product, Engineering, Sales, and Marketing. You will shape positioning, messaging, launches, customer engagement, analyst relations, competitive strategy, sales enablement, and demand generation. Think of this as joining an early-stage AI startup backed by an established public company. What You’ll Own - Own the go-to-market strategy for the Agentic Observability Platform. - Develop differentiated messaging, positioning, and value propositions. - Build competitive intelligence on emerging AI observability, evaluation, and governance vendors. - Partner with Product and Engineering to shape the roadmap based on customer feedback and market trends. - Lead product launches and release communications. - Develop customer-facing content including: - Website messaging - Product pages - Solution briefs - White papers - Case studies - Demo scripts - Sales presentations - Enable Sales through: - Battle cards - Competitive positioning - Discovery guides - Objection handling - Pricing support - Demo narratives - Partner with Demand Generation on: - Campaign strategy - Landing pages - Webinars - Digital advertising - Content strategy - Conduct customer interviews to continuously refine messaging. - Represent Innodata at conferences, webinars, customer meetings, and industry events. - Support analyst and media briefings. - Become an internal expert on AI evaluation, observability, governance, agentic AI, and enterprise adoption. Qualifications - 7+ years of Product Marketing experience. - Experience launching enterprise B2B SaaS products. - Strong technical curiosity with the ability to understand AI platforms and developer technologies. - Excellent storytelling and presentation skills. - Experience working closely with Product Management and Engineering. - Ability to translate technical capabilities into business value. - Comfort operating in ambiguous, fast-moving startup environments. Preferred Experience - Experience with one or more of: - AI platforms - LLMs - Agentic AI - AI evaluation - AI observability - ML infrastructure - Developer platforms - Enterprise software - Experience marketing products to: - AI teams - Engineering leaders - CTOs - CIOs - Data science organizations Success Metrics (First 12 Months) - Launch a complete messaging and positioning framework. - Deliver world-class website and product content. - Build competitive intelligence for the AI observability market. - Enable Sales with comprehensive GTM assets. - Support major product launches and customer announcements. - Improve product awareness, pipeline contribution, and win rates. - Establish Innodata as a recognized thought leader in Agentic AI evaluation and observability. Characteristics - Entrepreneurial - Customer obsessed - Technically curious - Strategic but highly execution oriented - Comfortable wearing multiple hats - Data driven - Excellent writer - Strong presenter - Collaborative across Engineering, Product, Sales, and Marketing This is a foundational hire that will help define the future of Innodata’s Agentic Observability business. The expected salary range for this position is $– $ USD per year, based on experience, skills, and qualifications. 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 Commission’s 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 verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Role Description We are seeking a highly analytical and AI-savvy Strategic Market Intelligence Manager to become the intelligence hub for our Marketing and Sales organizations. This role will provide actionable insights into markets, competitors, customers, buying signals, and emerging AI trends that directly influence product strategy, demand generation, sales priorities, executive decision-making, and go-to-market execution. The ideal candidate is naturally curious, data-driven, technically proficient, and passionate about understanding rapidly evolving AI markets. What You’ll Own - Market Intelligence - Monitor AI industry trends, emerging technologies, and market dynamics. - Conduct market sizing (TAM, SAM, SOM) and growth analyses. - Research emerging customer use cases across Innodata’s six practice areas. - Identify new vertical and geographic expansion opportunities. - Produce executive-ready market reports and recommendations. - Competitive Intelligence - Track competitors’ product launches, messaging, pricing, partnerships, acquisitions, and funding. - Develop and maintain competitive battle cards. - Analyze competitor strengths, weaknesses, positioning, and go-to-market strategies. - Deliver competitive briefings to Sales, Product Marketing, and Executive Leadership. - Maintain a centralized competitive intelligence repository. - Buying Signals & Account Intelligence - Monitor funding announcements, executive hires, acquisitions, AI initiatives, partnerships, and technology adoption. - Identify companies showing strong intent to invest in AI initiatives. - Partner with Sales and SDR teams to prioritize target accounts based on buying signals. - Leverage intent data and publicly available information to uncover new opportunities. - Customer & Industry Research - Analyze customer trends and purchasing behavior. - Conduct win/loss analysis in partnership with Sales. - Identify changes in buyer personas and decision-making processes. - Recommend updates to ideal customer profiles and market segmentation. - Executive Insights - Develop recurring executive briefings that summarize: - Market developments - Competitive activity - Emerging AI trends - Strategic opportunities - Business risks - Recommended actions - Present findings regularly to Marketing, Sales Leadership, Product Management, and Executive Leadership. - AI-Powered Intelligence - Design and continuously improve AI-driven workflows to automate: - Competitive monitoring - News aggregation - Executive movement tracking - Funding alerts - Product launch monitoring - Industry research - Buying signal detection - Leverage AI tools to improve research quality, speed, and scalability. Qualifications - 5+ years of experience in market intelligence, competitive intelligence, product marketing, strategy consulting, market research, or related analytical roles. - Strong analytical and research skills. - Exceptional written and verbal communication skills. - Experience synthesizing complex technical and market information into concise executive recommendations. - Ability to work independently in a fast-paced, evolving environment. Requirements - Experience in one or more of the following: - Artificial Intelligence - Machine Learning - Enterprise Software - SaaS - Cloud Computing - Data Platforms - Developer Tools - Experience using research platforms such as: - Crunchbase - CB Insights - PitchBook - Gartner - IDC - Forrester - LinkedIn Sales Navigator - Similarweb - SEMrush - ZoomInfo - 6sense - Experience using AI tools such as ChatGPT, Claude, Gemini, Perplexity, NotebookLM, or other AI research platforms. Success Metrics (First 12 Months) - Establish a repeatable competitive intelligence program. - Build a centralized intelligence repository accessible to Marketing and Sales. - Deliver weekly executive intelligence briefings. - Produce actionable buying signal reports that contribute to pipeline generation. - Improve sales effectiveness through high-quality competitive insights and battle cards. - Refine Innodata’s ICPs and market segmentation using data-driven insights. - Develop AI-powered workflows that significantly reduce manual research time. - Become the organization’s trusted source for market and competitive intelligence. Personal Characteristics - Naturally curious - Strategic and analytical - Highly organized - Proactive and self-directed - Comfortable working with executives - Passionate about AI and emerging technologies - Skilled at connecting data to business decisions - Collaborative across Marketing, Product, Sales, and Executive Leadership The expected salary range for this position is $– $ USD per year, based on experience, skills, and qualifications. 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 Commission’s guide at FTC Job Scams . If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Role Description We are looking for a curious and driven Data Engineering Intern to join our Data & AI team. You will primarily focus on building and maintaining robust data pipelines and infrastructure, while also contributing to applied AI projects involving Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems. This is a hands-on role. You will work alongside senior engineers and data scientists, contributing to production-grade systems. The role is roughly 65% Data Engineering and 35% Data Science / Applied AI. What You’ll Own - Data Engineering - Design, build, and maintain scalable ETL/ELT data pipelines using tools like Apache Airflow, dbt, or Spark - Work with structured and unstructured data from various sources — APIs, databases, event streams - Write optimized SQL queries and data transformation logic for analytical and ML use cases - Maintain and improve data quality, schema management, and pipeline monitoring - Collaborate on data warehouse and data lake architecture (e.g., Snowflake, BigQuery, Delta Lake) - Document data flows, lineage, and schema definitions - Data Science & Applied AI - Build and evaluate RAG pipelines — chunking, embedding, indexing, and retrieval - Work with vector databases (e.g., Pinecone, Weaviate, pgvector) for semantic search - Integrate LLM APIs (OpenAI, Anthropic, open-source models) into data products or internal tools - Help with prompt engineering, evaluation frameworks, and fine-tuning experiments - Support exploratory data analysis and feature engineering for ML workflows Qualifications - Pursuing a degree in Computer Science, Data Science, Engineering, or a related field - Solid foundation in Python — comfortable writing clean, modular, production-quality code - Hands-on experience with SQL (query optimization, CTEs, window functions) - Familiarity with at least one cloud platform — AWS, GCP, or Azure - Understanding of data pipeline concepts: batch vs streaming, orchestration, idempotency - Strong analytical mindset with attention to data quality and correctness - Experience with workflow orchestrators: Apache Airflow, Prefect, or Dagster - Exposure to dbt for data transformation and testing Requirements - The expected hourly range for this position is $20/hour. Important Notice 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 Commission’s 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 verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Role Description 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 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. 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 Own - Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Labeling elements of a piece of content rather than the content as a whole. - Assigning predefined categories or labels to items. - Evaluating the perceived quality and/or appropriateness of content. - Generating labels to advance understanding of a concept, trend, etc. - 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. - Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. - Ordering or ranking items based on a set of preferences or criteria. - Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). - Generating responses to prompts or questions using a language model or other AI system. - Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. - Producing concise summaries of longer pieces of text or data. - Converting spoken language or audio content into written text. - Converting text or spoken language from one language to another. - 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. 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 Turkish. Requirements - The expected hourly salary range for this position is $15 p/hour, based on experience, skills, and qualifications. Company Description 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 Commission’s 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 verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Role Description 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 Data Annotators 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. 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 Own - Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Labeling elements of a piece of content rather than the content as a whole. - Assigning predefined categories or labels to items. - Evaluating the perceived quality and/or appropriateness of content. - Generating labels to advance understanding of a concept, trend, etc. - 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. - Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. - Ordering or ranking items based on a set of preferences or criteria. - Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). - Generating responses to prompts or questions using a language model or other AI system. - Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. - Producing concise summaries of longer pieces of text or data. - Converting spoken language or audio content into written text. - Converting text or spoken language from one language to another. - 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. Qualifications - A High School Diploma or higher is required. - Professional or Expert level proficiency (C1/C2) in English. Requirements - The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Important Information 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 Commission’s guide at FTC Job Scams . If you believe you’ve been targeted by a recruitment scam, please report it to Innodata at verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Role Description 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 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. 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 Own - Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Labeling elements of a piece of content rather than the content as a whole. - Assigning predefined categories or labels to items. - Evaluating the perceived quality and/or appropriateness of content. - Generating labels to advance understanding of a concept, trend etc. - 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. - Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. - Ordering or ranking items based on a set of preferences or criteria. - Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). - Generating responses to prompts or questions using a language model or other AI system. - Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. - Producing concise summaries of longer pieces of text or data. - Converting spoken language or audio content into written text. - Converting text or spoken language from one language to another. - 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. 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. Requirements - The expected hourly salary range for this position is $15 p/hour, based on experience, skills, and qualifications. Important Information 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 Commission’s 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 verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Role Description 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 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. 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 Own - Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Labeling elements of a piece of content rather than the content as a whole. - Assigning predefined categories or labels to items. - Evaluating the perceived quality and/or appropriateness of content. - Generating labels to advance understanding of a concept, trend, etc. - 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. - Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. - Ordering or ranking items based on a set of preferences or criteria. - Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). - Generating responses to prompts or questions using a language model or other AI system. - Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. - Producing concise summaries of longer pieces of text or data. - Converting spoken language or audio content into written text. - Converting text or spoken language from one language to another. - 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. 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. Requirements - The expected hourly salary range for this position is $15 p/hour, based on experience, skills, and qualifications. Company Description 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 Commission’s 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 verifyjoboffer@innodata.com and consider reporting it to the FTC at ReportFraud.ftc.gov .

Role Description 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 Data Annotation 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 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. 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 Own - Rating/assessing the performance of AI models or algorithms based on their output or behavior through a set of evaluative questions. - Labeling elements of a piece of content rather than the content as a whole. - Assigning predefined categories or labels to items. - Evaluating the perceived quality and/or appropriateness of content. - Generating labels to advance understanding of a concept, trend etc. - 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. - Reviewing data and identifying whether or not a product feature works as intended based on the project's guidelines. - Labeling model outputs to identify if a piece of content is or isn't something. Examples: identify clickbait; identifying gaming videos; identifying branded content. - Ordering or ranking items based on a set of preferences or criteria. - Creating prompts or questions that will be used to generate responses from a language model or other AI system. - Projects that evaluate the relevance of content based on a relevancy scale (1-3, 1-5, etc.). - Generating responses to prompts or questions using a language model or other AI system. - Rewriting existing text while preserving the original meaning, often to improve clarity or style and adherence to guidelines. - Producing concise summaries of longer pieces of text or data. - Converting spoken language or audio content into written text. - Converting text or spoken language from one language to another. - 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. Qualifications - A High School Diploma or higher is required. - Professional or Expert level proficiency (C1/C2) in English. Requirements - The expected hourly salary range for this position is $9 p/hour, based on experience, skills, and qualifications. Company Description Innodata (Nasdaq: INOD) is a global data engineering company. We believe that data and Artificial Intelligence (AI) are inextricably linked. Our mission is to enable the responsible advancement of artificial intelligence by providing the data, evaluation frameworks, and human expertise required to build AI systems that can be trusted at scale. We provide a range of transferable solutions, platforms, and services for Generative AI / AI builders and adopters. In every relationship, we honor our 36+ year legacy delivering the highest quality data and outstanding outcomes for our customers.