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Location: In Office - San Jose, California 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. Scope of the Role: We are standing up a dedicated onsite team to evaluate complex, real-world agentic AI workflows for a frontier AI customer. Reviewers work through ambiguous, multi-step scenarios inside isolated test environments, assessing whether AI agents complete tasks safely, respect user intent and consent, and hold up under close scrutiny. The Quality Lead is the person accountable for whether that output is any good. This is a senior individual contributor role. You will not manage the reviewers — that sits with the Engagement Manager — but you set the standard they are held to. You own the audit sample, run calibration, keep the rubric usable as real cases stress it, and train reviewers into the work. You are also the deputy: when the Engagement Manager is out, the engagement runs on you. The quality approach here is not fully defined. We expect you to build it in partnership with the customer's quality leads, or at minimum to take what they have, run it honestly, and come back with specific recommendations for where it falls short. What You’ll Own: Own the quality system for the engagement: audit design, sampling strategy, scoring standards, and how quality gets measured and reported Build that system with the customer's quality leads where none exists, and where one does, operate it and recommend concrete improvements based on what the data shows Re-score a sample of reviewer output as a second pass; identify error patterns rather than isolated mistakes Run calibration sessions: surface disagreement, work it to resolution, and document the reasoning so the outcome holds for future cases Maintain rubric health — flag criteria that are ambiguous, overlapping, or silent on cases the team keeps hitting, and drive revisions through the customer Train and onboard new reviewers, including nesting plans, ramp criteria, and the judgment call on when someone is production-ready Give the Engagement Manager the evidence behind performance conversations: who is drifting, on what, and whether coaching is working Report quality trends to the Engagement Manager and, alongside them, to the customer Deputize for the Engagement Manager on delivery operations during absences Maintain information security, privacy, and facility access practices required by the customer's onsite environment You’ll Thrive in This Role If You Have: Bachelor's degree or equivalent practical experience 4+ years in quality assurance, quality management, or senior review work within annotation, evaluation, trust and safety, or a similarly judgment-intensive domain Direct experience owning a quality function: you designed the audit, not just executed someone else’s Significant experience with AI/ML evaluation work: annotation, red-teaming, RLHF, model or agent evaluation, or trust and safety review Hands-on familiarity with agentic systems: tool use, multi-step task execution, sandboxed environments, and common failure modes Demonstrated ability to run calibration with peers — including holding a position under disagreement and changing it when the argument is better Strong written communication; able to document a scoring standard clearly enough that a reviewer can apply it and an auditor can check it Comfortable in spreadsheets and in a dashboarding tool, with enough Python or SQL to pull and slice your own data (you will not be asked to build interfaces) Experience training or onboarding reviewers into rubric-based work The expected hourly salary range for this position is $75-85 p/hour, 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 .

Location: In Office - San Jose, California 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. Scope of the Role: We are standing up a dedicated onsite team to evaluate complex, real-world agentic AI workflows for a frontier AI customer. The Engagement Manager owns this team and this engagement: a group of ten reviewers and one QA lead working inside isolated test environments, assessing whether AI agents complete tasks safely, respect user intent and consent, and hold up under close scrutiny. This is a delivery leadership role with a strong customer-facing component. You are the customer's primary day-to-day contact at the site, accountable for throughput, quality, and turnaround, and responsible for identifying where the engagement should grow next. You will not be scoring trajectories as a daily task, but you need enough technical depth to audit the team's work yourself and defend a scoring decision in a room with the customer's technical leads. What You’ll Own: Own end-to-end delivery for the onsite team: throughput, quality, turnaround, and capacity against committed volumes Manage and develop a team of eleven, including hiring, onboarding, performance management, and retention Serve as the primary onsite point of contact for the customer's program and technical leads; run recurring reviews, report on delivery metrics, and resolve issues before they escalate Audit reviewer output directly — sample trajectories, check rubric application, and assess whether scoring rationale would survive customer review Partner with the QA lead on calibration cycles, quality metrics and evaluation, and rubric refinement; arbitrate disagreements that calibration does not resolve Own the escalation path for safety-relevant and ambiguous findings, including judgment on what reaches the customer and how quickly Identify expansion opportunities within the account: adjacent workstreams, new task types, additional capacity, and scope the work with internal delivery and commercial teams Forecast staffing and cost against the engagement's commercial model, and flag variance early Maintain information security, privacy, and facility access practices required by the customer's onsite environment You’ll Thrive in This Role If You Have: Bachelor's degree or equivalent practical experience 5+ years of professional experience, including direct management of a delivery team of 10–20 people Track record as the customer-facing owner of a services or delivery engagement with an enterprise or technology client, including metrics reporting and issue escalation Significant experience with AI/ML evaluation work: annotation, red-teaming, RLHF, model or agent evaluation, or trust and safety review Ability to read rubric-scored work critically and form an independent view of whether a score is correct Strong written communication; able to produce reporting and escalation memos that a technical customer will accept without rework The expected hourly salary range for this position is $75-85 p/hour, 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 .

Location: Remote - United States 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 Overview We are seeking detail-oriented evaluators to conduct human quality evaluations for an enterprise AI customer support product on Instagram, WhatsApp, and Messenger. You will evaluate and benchmark AI model responses against complex evaluation rubrics using provided business knowledge bases. What You’ll Own: Model Evaluation: Review and score AI-generated customer interactions across Foundational, Experiential, and Operational dimensions (e.g., Action Fidelity, Faithfulness, Hallucination, Compliance, Tone, and Handoff). Intent & Fact Verification: Benchmark both informational (R1) and transactional (R2) customer queries against authoritative business sources (FAQs, product catalogs, SOPs) within the task UI. Quality Assurance: Participate in dual-review processes and daily calibration audits to ensure inter-rater agreement and establish ground-truth performance targets. Performance Targets: Deliver precise evaluation You’ll Thrive in This Role If You Have: Customer Service Background: Prior experience in customer service, call centers, retail, or handling customer communications via email, chat, or phone (highly prioritized). English Proficiency: Exceptional written English skills with a strong command of tone, brand voice, grammar, and nuance. French Proficiency: Exceptional written French skills with a strong command of tone, brand voice, grammar, and nuance. Analytical Precision: Ability to strictly follow multi-tier evaluation guidelines, complex logic trees, and technical rubrics without deviation. Tech Adaptability: Comfort using dedicated web-based tools and labeling interfaces. 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 .

Location: Hybrid - Washington D.C 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. About this Role: Produce high-fidelity annotations on imagery and video used to train and evaluate machine learning models. Annotators work to a defined ontology and labeling specification, meet project quality and throughput targets, and operate inside the designated annotation environment for each program. Assignments rotate across projects, modalities, and customers as program needs change. Key Responsibilities: Label static imagery and video across a range of sensor types, image qualities, and scene conditions, including both real-world and synthetic data. Produce 2D bounding boxes, instance and semantic segmentation masks, and keypoint annotations to project specification. Produce oriented and rotated bounding boxes where scene geometry requires them. Produce 3D and 6 degrees-of-freedom pose, orientation, and scale annotations on projects that require them. Produce multi-object tracking annotations, maintaining consistent object identity across full sequences — through occlusion, frame exit and re-entry, scale change, and camera or platform motion. Review, correct, and accept or reject model-assisted and pre-labeled output; report systematic pre-label failure modes rather than silently correcting the same error frame by frame. Work strictly to the project ontology and guidelines; escalate ambiguous or out-of-ontology objects rather than guessing. Meet assigned accuracy and throughput targets, and hold that standard consistently across large batches. Complete rework promptly from QA feedback, applying the correction to comparable cases in the same batch. Log edge cases and recurring ambiguities so they can be adjudicated and folded into the guidelines. Follow all customer data-handling, confidentiality, and information security requirements for the assigned project, and keep required training current. Must-Have Qualifications: 1+ years of image or video annotation experience, or equivalent precision work in a quality-managed production environment. Working familiarity with at least one professional annotation platform (for example CVAT, V7 Darwin, Labelbox, Scale, or comparable). Practical understanding of bounding boxes, segmentation masks, keypoints, and object tracking — and of what makes each one correct rather than merely present. Strong visual attention to detail and the discipline to hold a standard across tens of thousands of frames. Ability to follow written labeling guidelines exactly, and to ask precise questions when they are silent on a case. Comfortable working in remote-desktop or browser-based environments. Nice-to-Have Qualifications: Experience across multiple annotation modalities rather than a single task type. Experience with aerial, overhead, satellite, or thermal/IR imagery. Experience with long-form video and tracking work. Experience reviewing model-assisted pre-labels in a human-in-the-loop pipeline. Prior work on government or regulated-industry programs. The expected hourly salary range for this position is $42,000 to $62,500 annually, based on experience, skills, and qualifications. Program eligibility: Some programs require eligibility for a government background investigation or credentialing. Assignment to those programs is contingent on meeting those requirements. 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 .

Location: Remote - United States 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 Overview We are seeking detail-oriented evaluators to conduct human quality evaluations for an enterprise AI customer support product on Instagram, WhatsApp, and Messenger. You will evaluate and benchmark AI model responses against complex evaluation rubrics using provided business knowledge bases. What You’ll Own: Model Evaluation: Review and score AI-generated customer interactions across Foundational, Experiential, and Operational dimensions (e.g., Action Fidelity, Faithfulness, Hallucination, Compliance, Tone, and Handoff). Intent & Fact Verification: Benchmark both informational (R1) and transactional (R2) customer queries against authoritative business sources (FAQs, product catalogs, SOPs) within the task UI. Quality Assurance: Participate in dual-review processes and daily calibration audits to ensure inter-rater agreement and establish ground-truth performance targets. Performance Targets: Deliver precise evaluation You’ll Thrive in This Role If You Have: Customer Service Background: Prior experience in customer service, call centers, retail, or handling customer communications via email, chat, or phone (highly prioritized). English Proficiency: Exceptional written English skills with a strong command of tone, brand voice, grammar, and nuance. Vietnamese Proficiency: Exceptional written Vietnamese skills with a strong command of tone, brand voice, grammar, and nuance. Analytical Precision: Ability to strictly follow multi-tier evaluation guidelines, complex logic trees, and technical rubrics without deviation. Tech Adaptability: Comfort using dedicated web-based tools and labeling interfaces. The expected hourly salary range for this position is up to $20 p/hour, 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 .

Location: Remote - United States 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. Scope of the Role: Help train the next generation of robots and AI by recording yourself completing simple, everyday household tasks. As a Robotic Data Collection Tester, you’ll wear a head-mounted camera and follow easy instructions while your movements and activities are recorded. This is a flexible opportunity that can be completed for up to 4 hours per day from a quiet environment. What You’ll Own: Wear a head-mounted camera/sensor while performing everyday activities such as cooking, cleaning, organizing, or using household objects. Follow scripted or natural task instructions while being recorded. Demonstrate realistic human movements that can be used to train and evaluate robotics/AI systems. Repeatedly perform tasks while maintaining consistent procedures and safety standards. Review recordings for quality and report technical issues with the equipment. No robotics programming experience may be required; attention to detail and comfort being recorded are important. You’ll Thrive in This Role If You Have: Recent iPhone or Android smartphone with a working camera. Ability to work up to 4 hours per day . Ability to work in a quiet, distraction-free environment . Comfortable wearing a head-mounted camera/strap and being recorded while completing everyday household tasks. Ability to follow simple instructions and repeat tasks consistently. Reliable internet connection and ability to upload recorded data, if required. Attention to detail and willingness to follow safety and privacy guidelines The expected hourly salary range for this position is $10-$12 p/hour, 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 .

Location: Remote - United States 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. Scope of 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 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. You’ll Thrive in This Role If You Have: PHD is required Professional or Expert level proficiency (C1/C2) in English The expected hourly salary range for this position is $25-$30 p/hour, 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 .

Location: Hybrid - Washington D.C 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. About the Program: Innodata's Federal Practice builds the trusted data layer for critical infrastructure Trust & Safety work. Partnering with a leading systems integrator, we're delivering a modern, governed data services platform in a secure federal (IL4) environment. Over an intensive 20-week phase, you'll help stand up a data services storefront, a DataCard governance framework, synthetic data integration, and Databricks write-back capabilities. About the Role: As the QA/Evaluation Lead, you'll own quality and evaluation across the platform. You'll design the evaluation framework that measures whether our data services and outputs meet the bar, build repeatable test and validation processes, and give the team an objective read on readiness at each milestone. Partnering with the Delivery Owner and engineering leads, you'll turn quality from an afterthought into a measurable, demonstrable strength. It's a role for someone who thinks rigorously about evaluation and takes pride in evidence-backed quality. Key Responsibilities: Design and own the inter-annotator agreement (IAA) methodology for the Phase 1 demonstration corpus — metric selection (Cohen's kappa, Fleiss, Krippendorff's alpha), sampling design, adjudication workflow, and agreement thresholds Define evaluation framework architecture: test and evaluation plans, IAA targets, drift detection gates, and model performance metrics per SOW Section 2.9 Configure and operate sampling-based quality control across the self-service and white-glove annotation paths during Phase D corpus production Design and implement confidence-threshold escalation routing from automated annotation to senior-annotator adjudication Validate quality scoring and IAA computation within the Innodata data layer Support AI Solutions Engineer on evaluation design for SAM 2 and Frontier model API validation — define what 'good enough' looks like quantitatively Produce evaluation framework documentation for the Phase 1 NPP closeout package, including per-DataCard documentation with the SA Must-Have Qualifications: Bachelor's degree in Statistics, Data Science, Computer Science, or related quantitative field required; Master's degree preferred. Equivalent experience may substitute for degree on a 2-for-1 basis. 6+ years total professional experience, 4+ years in data quality, evaluation methodology, or QA on AI/ML programs IAA methodology expertise — Cohen's kappa, Fleiss' kappa, Krippendorff's alpha: hands-on, not theoretical Evaluation framework design for AI/ML training data programs QC process design: sampling methodology, escalation workflows, adjudication protocols Python for QC tooling, metric computation, and statistical analysis Active Secret clearance with TS/SCI eligibility Nice-to-Have Qualifications: Prior DoD or IC data quality program experience CVAT or equivalent annotation platform QC workflow configuration Drift detection and model monitoring methodology Experience with FMV / video annotation quality standards The expected hourly salary range for this position is $45 to $50 p/hour, based on experience, skills, and qualifications. Note to Candidates: This role is not a project manager with QC responsibilities — it is a methodology expert who owns the intellectual framework behind data quality on a federal AI program. The right candidate can walk into a meeting with Government evaluators and explain exactly why the evaluation design produces trustworthy labels. That conversation is part of Phase 2 positioning. 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 .

Location: Hybrid - Washington D.C 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. About the Program: Innodata's Federal Practice builds the trusted data layer for critical infrastructure Trust & Safety work. Partnering with a leading systems integrator, we're delivering a modern, governed data services platform in a secure federal (IL4) environment. Over an intensive 20-week phase, you'll help stand up a data services storefront, a DataCard governance framework, synthetic data integration, and Databricks write-back capabilities. About the Role: As the Solution Architect, you'll design the backbone of the platform. You'll define the architecture for the data services storefront and own the DataCard governance framework that keeps our data trustworthy, documented, and compliant end to end. Working closely with the engineering team and the Delivery Owner, you'll translate governance and security requirements in a secure federal (IL4) environment into a clean, defensible technical design. It's a role for an architect who cares as much about data stewardship and governance as about elegant systems. Key Responsibilities: Own cross-pillar architectural integrity and interface coordination across the 24-week program Design and stand up the DataCard governance framework: schema design, distribution-statement methodology (DoD Dir. 5230.24), provenance lineage Deploy and configure ZenML multi-cloud orchestration stack per Innodata Layer 2 Multi-Cloud Architecture v3 Design taxonomy engine and sequestration controls architecture Confirm NIST SP 800-53 Rev 5 control split between Innodata data-layer and AFS infrastructure-layer scope Lead platform component run books and per-DataCard documentation in Phase E Coordinate with AI Solutions Engineer on Kubernetes-adjacent data-layer DLP policy configuration Coordinate with Backend Engineer on Databricks write-back schema and DataCard write-back path Must-Have Qualifications: Bachelor's degree in Computer Science, Data Engineering, or related field required; Master's degree preferred. Equivalent experience may substitute for degree on a 2-for-1 basis. 10+ years total professional experience, 6+ years in data architecture or platform engineering Databricks, Delta Lake, and MLflow — hands-on implementation experience, not conceptual Data governance frameworks: DataCards, provenance, lineage, distribution statement controls ZenML or equivalent ML orchestration tooling (Airflow or Prefect acceptable; must be willing to ramp ZenML quickly) Working knowledge of IL4/IL5 boundary concepts, NIST SP 800-53 Rev 5, and DoD data classification requirements Active Secret clearance with TS/SCI eligibility Nice-to-Have Qualifications: Prior Innodata or annotation platform architecture experience MLflow model governance and registry hands-on experience Ontology and taxonomy design for AI/ML training datasets DoD Directive 5230.24 distribution statement implementation experience The expected hourly salary range for this position is $70 to $75 p/hour, based on experience, skills, and qualifications. Note to Candidates: This role is the primary technical decision-maker on the program below the Delivery Owner. The SA is expected to make architectural calls independently within the established framework and surface only unresolved cross-cutting decisions to the Delivery Owner. 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 .

Location: Hybrid - Washington D.C 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. About the Program: Innodata's Federal Practice builds the trusted data layer for critical infrastructure Trust & Safety work. Partnering with a leading systems integrator, we're delivering a modern, governed data services platform in a secure federal (IL4) environment. Over an intensive 20-week phase, you'll help stand up a data services storefront, a DataCard governance framework, synthetic data integration, and Databricks write-back capabilities. About the Role: As the Data/Annotation Engineer, you'll be hands-on with the data itself. You'll administer the annotation toolchain, manage annotation workflows across the corpus, and produce the per-dataset documentation that feeds our governance framework. You'll work with the AI Solutions Engineer to ensure the data going into our models is accurate, well-labeled, and fully traceable. This role is for someone detail-obsessed who understands that great AI starts with disciplined, well-governed data. Key Responsibilities: Receive, validate, ingest, and ontology-map the ODIN mission-aligned corpus from AFS delivery Produce the ODIN load report: corpus description, ontology mapping, readiness state Configure CVAT annotation pipeline against the Phase 1 starter kit rule pack Operate both self-service and lightweight white-glove annotation paths during Phase D corpus production Produce 50–100 label demonstration corpus across synthetic and mission-aligned content Support QA/Evaluation Lead on QC execution and corpus annotation dry-runs Associate DataCard provenance records with annotated and synthetic outputs in coordination with the Solution Architect Must-Have Qualifications: Bachelor's degree in Data Science, Computer Science, or related field preferred. Equivalent experience may substitute for degree on a 2-for-1 basis. 5+ years total professional experience, 3+ years in data engineering or annotation operations CVAT — deployment and day-to-day operation required; this is not a nice-to-have Annotated dataset ingest pipelines: schema mapping, format validation, ontology alignment Full-motion video (FMV) annotation concepts and tooling Python scripting for data wrangling, validation, and format conversion Active Secret clearance with TS/SCI eligibility Nice-to-Have Qualifications: Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field required; Master's degree preferred. Equivalent experience may substitute for degree on a 2-for-1 basis CVAT annotation platform — AI feature configuration and operation DoD or IC data program experience: CUI, distribution statements, federal data governance Evaluation design for AI/ML training data: IAA methodology, drift detection, model performance measurement Video understanding or FMV annotation experience DataCard or ML data provenance framework familiarity The expected hourly salary range for this position is $55 to $60 p/hour, based on experience, skills, and qualifications. Note to Candidates: Phase D corpus production (Weeks 17–19) is the core demonstration deliverable. Candidates must be genuinely comfortable operating CVAT at production quality against a mission dataset under a milestone deadline 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 .

Location: Hybrid - Washington D.C 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. About the Program: Innodata's Federal Practice builds the trusted data layer for critical infrastructure Trust & Safety work. Partnering with a leading systems integrator, we're delivering a modern, governed data services platform in a secure federal (IL4) environment. Over an intensive 20-week phase, you'll help stand up a data services storefront, a DataCard governance framework, synthetic data integration, and Databricks write-back capabilities. About this Role: As the Backend/Integration Engineer, you'll build the connective tissue of the platform. You'll develop the data services storefront's backend, stand up ingest pipelines, and implement reliable write-back into our data lakehouse so results flow cleanly across systems. Working alongside the Solution Architect, you'll make sure the platform's components integrate securely and perform under real workloads in a federal (IL4) environment. It's a strong fit for a backend engineer who likes owning integrations and turning architecture into working plumbing. Key Responsibilities: Implement Databricks REST API write-back for labeled outputs, DataCard provenance records, and synthetic content outputs Build and validate the Duality back-end integration: catalog intake form configuration, parameter translation to Duality generation API, async job lifecycle management (submission, tracking, retry, completion), output handling Implement ServiceNow REST integration for white-glove routing intake path Build and maintain storefront backend services (API layer between frontend UI and platform components) Implement DataCard write-back path in coordination with Solution Architect Design and maintain async job queue management and retry logic across all integration surfaces Structure output metadata for DataCard provenance records per DoD distribution statement requirements Must-Have Qualifications: Bachelor's degree in Computer Science, Software Engineering, or related field required. Equivalent experience may substitute for degree on a 2-for-1 basis. 6+ years total professional experience, 4+ years backend or API integration engineering Python backend development — strong, production-grade REST API integration with async job lifecycle patterns (submission, polling, retry, webhook handling) Databricks REST API or strong Spark/Databricks platform familiarity JSON schema design and structured metadata handling Active Secret clearance with TS/SCI eligibility Nice-to-Have Qualifications: ServiceNow REST API integration experience Federal program API integration background ZenML or ML orchestration pipeline familiarity React or modern frontend experience for storefront skeleton support The expected hourly salary range for this position is $75 to $80 p/hour, based on experience, skills, and qualifications. Note to Candidates: The Databricks write-back and Duality integration are the two highest-complexity tasks in Phase B. Candidates should be prepared to discuss async API integration patterns and their approach to retry logic and error handling in federal-data environments during the interview. 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 .

Location: Hybrid - Washington D.C 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. About the Program: Innodata's Federal Practice builds the trusted data layer for critical infrastructure Trust & Safety work. Partnering with a leading systems integrator, we're delivering a modern, governed data services platform in a secure federal (IL4) environment. Over an intensive 20-week phase, you'll help stand up a data services storefront, a DataCard governance framework, synthetic data integration, and Databricks write-back capabilities. About the Role: As the AI Solutions Engineer, you'll bring the platform's AI capabilities to life. You'll integrate synthetic data generation into the pipeline, stand up and tune the annotation toolchain, and orchestrate reproducible ML workflows that the rest of the team can build on. You'll partner with the Solution Architect and Data/Annotation Engineer to turn raw corpora into high-quality, model-ready data. This role suits an engineer who's fluent across modern AI tooling and enjoys making sophisticated ML infrastructure actually work in production. Key Responsibilities: Configure and validate native AI-assistive features across bundled platform components (Dataset Explorer, DataCard Service, Annotation Platform) Integrate and tune SAM 2 for full-motion video annotation: object tracking, segmentation calibration, confidence threshold configuration Implement Frontier model API integration for synthetic data fidelity validation: prompt engineering, response validation, quality scoring Configure AI-assisted annotation features: confidence scoring, auto-escalation triggers, model-assisted label suggestion Implement ICAM / OIDC authentication integration with AFS identity framework Configure data-layer DLP policies above the AFS-managed DLP infrastructure substrate Configure NiFi FMV codec validation layer (H.264, H.265, MPEG-4) above AFS-managed substrate Validate AI feature integration end-to-end across storefront, annotation platform, and DataCard write-back during Phase C Must-Have Qualifications: Bachelor's degree in Computer Science, Machine Learning, Data Science, or related field required; Master's degree preferred. Equivalent experience may substitute for degree on a 2-for-1 basis. 6+ years total professional experience, 4+ years hands-on AI/ML engineering SAM 2 or equivalent foundation model integration for computer vision or video annotation Frontier model API integration (OpenAI, Anthropic, or equivalent): async job management, quality validation pipelines Python — strong, production-grade; comfortable with ML tooling and data pipeline development Experience configuring AI-assistive features in annotation platforms or ML data tooling Active Secret clearance with TS/SCI eligibility Nice-to-Have Qualifications: CVAT annotation platform — AI feature configuration and operation DoD or IC data program experience: CUI, distribution statements, federal data governance Evaluation design for AI/ML training data: IAA methodology, drift detection, model performance measurement Video understanding or FMV annotation experience DataCard or ML data provenance framework familiarity The expected hourly salary range for this position is $75 to $80 p/hour, based on experience, skills, and qualifications. Note to Candidates: This role does not own infrastructure deployment. The AI Solutions Engineer operates at the AI/ML configuration and integration layer above the infrastructure. Ideal candidate is equally comfortable writing Python integration code and reasoning about model quality — and understands that in a federal data environment, every AI decision needs an audit trail. 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 .

Location: Remote - United States 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. Scope of 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 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. You’ll Thrive in This Role If You Have: 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 The expected hourly salary range for this position is $15 p/hour, 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 .

Location: Remote - Michigan 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. Scope of 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 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. You’ll Thrive in This Role If You Have: 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 The expected hourly salary range for this position is $15 p/hour, 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 .

Location: Remote - Massachusetts 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. Scope of 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 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. You’ll Thrive in This Role If You Have: 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 The expected hourly salary range for this position is $15 p/hour, 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 .

Location: Remote - Rhode Island 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. Scope of 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 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. You’ll Thrive in This Role If You Have: 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 The expected hourly salary range for this position is $15 p/hour, 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 .

Location: Remote - Nevada 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. Scope of 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 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. You’ll Thrive in This Role If You Have: 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 The expected hourly salary range for this position is $15 p/hour, 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 .

Location: Remote - Minnesota 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. Scope of 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 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. You’ll Thrive in This Role If You Have: 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 The expected hourly salary range for this position is $15 p/hour, 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 .