1271 Annotation Jobs - Page 9

Overview The Quality Control (QC) Specialist will play a critical role in ensuring the accuracy, consistency and quality of annotated legal documents. This role involves reviewing annotations created by annotators, validating metadata, and ensuring that each document meets the defined standards for tagging and categorisation. The QC Specialist will collaborate closely with annotators, tech team and project leads to maintain high standards across annotations for judgments, legal provisions, and opinions. Key Expectations from Role Quality Assurance and Accuracy Control Develop and implement quality metrics to ensure high standards for each annotated document, measuring accuracy rates, consistency, and adherence to guidelines. Identify and document any deviations from annotation standards, ensuring that each error is flagged, documented, and tracked to facilitate corrective actions. Perform random sampling and focused audits to verify annotation quality and reduce error rates across the project, providing a continuous check on data integrity. Annotation Review and Verification Conduct thorough reviews of annotations of judgments, legal provisions, and opinions to verify that annotations adhere to established standards. Cross-check each annotation for core legal elements, including case name, date, court name, statutory references, legal principles, and issues to ensure completeness. Ensure that metadata such as case identifiers, statutes cited, and legal doctrines are accurately and consistently tagged according to project guidelines. Validate that complex legal relationships are accurately identified in each document and recorded in standardized manner for ease of cross linking (e.g., judgments overruled, followed, referred, distinguished). Validate documents are timestamped correctly by annotators (e.g.: Date of pronouncement, date of publication of a notification in official gazette, date when provisions from the document came in effect from, etc.) Holistic Metadata Validation and Standardization Validate the accuracy and relevance of metadata extracted by annotators or automated tools, ensuring all extracted information meets required standards. Ensure uniformity across metadata fields such as case numbers, legal provisions, key legal outcomes, and cross-references. Confirm that all metadata follows the standardized structure and is formatted correctly for integration into the AI tool. Segmentation and Categorization Review Verify that judgments and legal provisions are segmented into appropriate categories, aligning with project requirements for legal classification (e.g., civil, criminal, appeal, petition). Ensure accurate tagging for legal relationships, including overruled, upheld, distinguished, or followed cases, to improve search functionality within the AI tool. Assess each document for proper categorization, ensuring uniform application of legal classifications across the dataset to enhance the AI tool’s contextual understanding. Feedback and Annotator Support Provide timely, constructive feedback to annotators on identified errors, suggesting corrective actions and reinforcing annotation standards. Document recurring errors or misunderstandings to guide annotator training, working with project leads to enhance guidelines and training materials. Quality Metrics Tracking and Reporting Maintain detailed records of quality metrics, documenting error rates, accuracy scores, and the frequency of specific annotation issues. Prepare regular quality reports summarizing review outcomes, highlighting any recurring issues and proposing corrective actions. Develop insights from quality control data to recommend improvements in annotation processes and guidelines, enhancing overall project quality. Collaboration and Process Improvement Collaborate with the Project Manager, Annotation Team Lead, and Technical Support teams to continually improve annotation standards and quality control processes. Share findings with cross-functional teams, contributing to the refinement of annotation guidelines, project workflows, and validation protocols. Actively participate in project meetings, providing insights on annotation quality, challenges, and recommendations for improvement. Documentation and Compliance Maintain meticulous records of all quality checks, ensuring that each document review is traceable, and that feedback is consistently documented. Adhere to data handling and confidentiality protocols, ensuring that all judgments, legal provisions, and opinions are reviewed in compliance with the firm’s standards for data security and privacy. Contribute to the development and refinement of QC documentation, including quality checklists, review protocols, and feedback guidelines. Recommended Qualifications Education : Bachelor’s degree in law, or a related field. Additional certifications in legal research or legal analytics are advantageous. Experience : Minimum of 2-3 years in a quality control, legal research, or data management role. Preferred : Experience in a legal knowledge management team with experience in document tagging, legal publishing house, or as a legal editor. Proven familiarity with legal document management, annotation standards, and legal taxonomy. Knowledge : Strong understanding of legal terminology and principles. Familiarity with annotation standards for legal texts. Knowledge of metadata standards and legal research databases is a plus. Skills : Exceptional attention to detail and analytical skills. Familiarity with legal research tools and annotation software. Holistic understanding of how legal data points interconnect and form a part of larger datasets Strong communication skills for providing feedback and training to annotators. Ability to work independently and collaboratively in a fast-paced project environment. Attributes : High degree of accuracy, ability to meet deadlines, and a commitment to maintaining confidentiality of legal documents.

Job Title: Python Code Quality Auditor – AI Annotation Review Experience: 5–8+ Years Location: Remote Role Overview: We are looking for a detail-oriented and experienced Python Code Quality Auditor to support our AI evaluation team. In this role, you will audit annotator evaluations of AI-generated Python code to ensure adherence to prompt instructions, functional correctness, and security standards. You will play a key role in maintaining high-quality benchmarks in Python code annotation and contributing to AI model training. Key Responsibilities: Review and audit annotator evaluations of AI-generated Python code for accuracy and completeness. Assess whether Python code adheres to prompt instructions, is functionally correct, and secure. Validate and test code snippets using proof-of-work methodology and appropriate execution tools. Identify errors or inconsistencies in annotator ratings or written explanations. Provide clear, constructive feedback to help maintain annotation quality and accuracy. Ensure all audits are conducted within the Project Atlas guidelines and maintain evaluation integrity. Document issues and findings in a structured and communicative manner. Required Qualifications: 5–8+ years of experience in Python development, code review, or QA. Strong understanding of Python syntax , debugging techniques , and edge case handling. Proficiency with writing and executing test cases using modern testing tools (e.g., unittest, pytest). Experience working in structured QA , annotation, or review workflows. Comfortable using code execution environments (e.g., Jupyter, REPLs, cloud IDEs). Excellent written communication and documentation skills. English proficiency at B2, C1, C2, or native level (required for reading and writing clear feedback). Preferred Skills (Nice to Have): Background in AI/ML , LLM evaluations, or prompt-based development. Experience with secure coding practices and code vulnerability analysis. Prior experience in technical annotation , content moderation, or crowdsourced QA platforms.

We are looking for English language Specialist, where you will immerse yourself in the exhilarating world of Large Language Models and Generative AI. We’re on the lookout for someone with an understanding of large language model and good in English proficiency as you need to clear the Versant Test to become eligible for the position. Responsibilities Review and edit English language content for grammar, punctuation, style, and tone. Collaborate with content creators, annotators, and other stakeholders to ensure consistency and quality across all communications. Assessing the quality of LLM outputs, identifying errors or inconsistencies, and providing detailed feedback using established rubrics. Develop and implement language guidelines and best practices. Provide cultural insights to ensure content resonates with target audiences. Required Hours: 25-30 hours per week Project Start Date: 9th July 2025 Required Test: Versant for English Eligibility: Only C1 & C2 scoring candidates in Versant test Share your Updated Resume/CV at ptomar@innodata.com to get assigned the Versant Test (Mention Subject Line as "English Expert" while sending emails) Qualifications Bachelor's degree in English, Linguistics, Communications, or a related field. Native or near-native proficiency in English. Proven experience in content creation, annotation, editing, or a similar role. Strong attention to detail and commitment to linguistic accuracy. Ability to work collaboratively in a fast-paced environment. Tier 1 & Tier 2 college Students or Pass outs are preferred Skills Excellent command of English grammar, syntax, and vocabulary. Strong editing and proofreading skills. Familiarity with content management systems (CMS). Effective communication and interpersonal skills. Cultural sensitivity and awareness.

DataLEADS is a strong and growing team that is driven by passion, creativity and collaboration. We value individuals with unique interests, experiences and who think differently. We’re committed to equal opportunities and creating an inclusive environment for all our team members. POSITION: ANALYST (DATA & ML) About the role: DataLEADS is seeking a highly motivated Data Analyst to join our dynamic, cross-functional team working at the intersection of media, technology, and public good. You’ll be responsible for managing data pipelines, building internal tools and dashboards, and supporting the deployment of AI/ML-powered workflows — especially for public health, digital media, and development-focused use cases. This role is ideal for someone with a strong technical foundation (Python, SQL, scripting) and an interest in automation, generative AI , and data-for-impact storytelling. Nature of Role Full time, from our office location in New Delhi Joining Immediate Requirements: Bachelor’s degree in Computer Science, Statistics, Engineering, Mathematics, or related technical field. Proficiency in Python, especially with libraries like pandas and requests; basic visualization using matplotlib or plotly Good command of SQL, including joins and common table expressions; familiarity with BigQuery or similar databases Basic JavaScript or Google Apps Script skills to support workflow automation Strong skills in Google Sheets or Excel (pivot tables, array formulas, basic macros) Exposure to using APIs (e.g., OpenAI, Claude) for prototyping or automation tasks Demonstrated interest in learning emerging tools in AI, automation, and data analysis Nice-to-Have Skills: Familiarity with tools like LangChain, Chroma, or vector search systems Basic experience building simple dashboards using Streamlit or Flask Exposure to data scraping or data collection using Python Understanding of or interest in working with data in areas like public health, misinformation, or digital media Key Responsibilities: Clean, transform, and enrich datasets using SQL and Google Sheets; maintain data views and internal dashboards Build and maintain automations using Google Apps Script, Zapier, and other no-code/low-code tools Write Python and JavaScript utilities to automate recurring tasks and retrieve external data Assist in prototyping AI/LLM-powered tools for tasks like annotation, summarization, and reporting — with support and supervision Create basic visualizations using Plotly or Matplotlib for internal and external stakeholders Document workflows, assumptions, and data logic clearly for team knowledge sharing What We Offer: At DataLEADS, you’ll have the opportunity to work on high-impact, real-world challenges , collaborate with an interdisciplinary team of technologists, journalists, and researchers, and gain hands-on exposure to cutting-edge tech interventions and frameworks . We offer a learning-focused, inclusive environment that encourages experimentation and growth. How to Apply: Send your CV, cover letter and links to portfolio (if available) to jobs@dataleads.co.in with the subject line: “Application: Data Analyst – [Your Name]” About DataLEADS: DataLEADS is a globally recognised digital media and tech company aimed to help people understand and engage with the world around them. We work on the complexity of a dynamic and evolving information ecosystem. Our work includes data intelligence, fact-checking initiatives, media and information literacy interventions, curriculum development, designing public policy interventions, media research, social listening and digital transformation. At the core of our work lies a profound belief that authentic information is central to human empowerment.

Bachelor degree on design/photography/fashion or any graduation with 3+ years related experience 2 + years demonstrating success managing a team with a track record of driving high performance Experience in fashion Strong oral (speaking, listening, interpretation) and written communication skills Strong analytical skills; you are someone who wants to dive into the numbers and seek to understand and has depth of experience in Excel Experience in understanding performance metrics and developing them, as required Demonstrated history delivering results in cross-functional environments; ability to drive organizational change using sound reasoning backed up by relevant data in a well-prepared business briefing A sense of urgency and an appreciation for working in a fast-paced, deadline-oriented environment Comfort with ambiguity; ability to be flexible in a rapidly changing environment The ML Data Annotation Services team within Amazon NA Store powers new products that deliver various CXs, using ML/AI to the fashion domain. Our team of Fashion Specialists provide high-quality labeled fashion data at high-speed and low-cost for Machine Learning (ML) and Computer Vision (CV) technologies, enabling delightful customer experiences. We partner with product and science teams to support launching new customer-facing fashion experiences and assist them throughout the product lifecycle. We're the team that thrives in a start-up like environment where flexibility, teamwork and ability to deliver solutions are a priority. You will have the opportunity to conceptualize, design and build AI driven experiences across the Amazon retail website and the Amazon Shopping mobile app. You will collaborate with various partner teams throughout Amazon and you will be a key member of a team that's building innovative new experiences that will change customers' lives. Amazon Fashion is revolutionizing how customers shop and buy clothing. Our business uses machine learning technology and stylist intuition to give great personalized recommendations based on customer preferences. If you are ready to work hard and engage in a rapidly changing industry, this position is right for you. We offer a creative, fast paced, entrepreneurial work environment where you’ll be driving various innovation at Amazon. We are looking for a Team Manager to build out and lead a team of annotation experts, who are fashion specialists, working closely with counterparts in the United States. The team you manage will annotate fashion images to provide data to train algorithms for fashion experiences across Amazon. The successful candidate will have a strong passion for design, photography, fashion and tech, a relentless desire to drive process improvement, and build a great team culture. Key job responsibilities Leading and developing a team of associates with fashion background Support the strategy for the team, drive clear goals and vision for initiatives Managing individual and team performance expectations and goals Working with third-party agencies and recruiting to recruit team members and onboard new hires Partnering with our training lead to develop and train Fashion Specialists and team managers and understanding and effectively utilize resources provided by internal systems, departments, policies, and procedures Developing our team practices and managing our workforce to create an exciting, supportive, ambitious and innovative culture Understanding different local fashion trends and deep diving into Amazon customers’ fashion preferences, and using this information to develop new styling strategies Delivering results quickly with little supervision in a dynamic and often ambiguous environment. Communicating effectively, including verbal and written skills, and influencing across levels Demonstrating strong business acumen, including problem solving skills, critical thinking, and a willingness to be vocally self-critical Exposure to process improvement/quality control tools and methods. Exceptional skills in data manipulation and analysis. Capacity planning. Proficiency in writing and understanding code. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Description Amazon is looking for an AI Content Expert II to help with annotations, content generation, and data analysis. As part of the Data Team, you will be responsible for delivering high-quality training data to improve and expand AGI's Large Language Models' (LLMs) capabilities. Note: This is a Fixed Term Contractual Role Key job responsibilities As an AI Content Expert, you will be responsible for creating training data that are complex in nature and will require you to make informed and high judgement decisions in each case. You will be working closely with scientists and engineers to review and update guidelines, identify tooling improvement opportunities, and engage in conversations regarding the quality of data. Creating and annotating high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content Writing grammatically correct texts in different styles with various degrees of creativity, stricly adhering to provided guidelines Performing audits and quality checks of tasks completed by other specialists, if required Making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks Diving deep into issues and implementing solutions independently Identifying and reporting tooling bugs and suggesting improvements A day in the life We are looking for a ML Data Associate (MLDA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech, text, audio, video data. Your ability to concentrate, multi-task and your high attention to detail helps you deliver high-quality work as well as maintaining strict confidentiality and follow all applicable Amazon policies for securing confidential information. You will be a part of a diverse team with the shared vision of improving customers’ lives with practical, useful generative AI innovations. An inner drive, individuality, and a creative mind are extremely beneficial. Basic Qualifications Bachelor’s degree in a relevant field or equivalent professional experience 2+ yrs of experience working with written language data, including experience with annotation, and other forms of data markup. Strong research skills to gather relevant information, understand complex topics, and synthesize multiple resources; understanding of basic academic integrity, i.e. plagiarism. Excellent attention to details and ability to focus for a long period of time Ability to effectively write and evaluate diverse subject matter across various domains* Ability to adapt writing style to suit various style guidelines and customers. Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy Preferred Qualifications Strong proficiency in English. Candidate must demonstrate excellent writing, reading, and comprehension skills (C1 level in the Common European Framework CEFR scale). Experience with creating complex data for LLM training and evaluation Strong understanding of U.S.-based culture, society, and norms. Comfortable with high-school level STEM* Familiarity with common markup languages such as HTML, XML, Markdown Familiarity with common standard text formats such as JSON, CSV, RTF Working knowledge of Python or another scripting language Familiarity with regular expressions syntax Familiarity with Large Language Models Comfort in annotation work that may include sensitive content Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - ADCI MAA 12 SEZ Job ID: A3027636

Description Amazon is looking for an AI Content Expert II to help with annotations, content generation, and data analysis. As part of the Data Team, you will be responsible for delivering high-quality training data to improve and expand AGI's Large Language Models' (LLMs) capabilities. Note: This is a Fixed Term Contractual Role Key job responsibilities As an AI Content Expert, you will be responsible for creating training data that are complex in nature and will require you to make informed and high judgement decisions in each case. You will be working closely with scientists and engineers to review and update guidelines, identify tooling improvement opportunities, and engage in conversations regarding the quality of data. Creating and annotating high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content Writing grammatically correct texts in different styles with various degrees of creativity, stricly adhering to provided guidelines Performing audits and quality checks of tasks completed by other specialists, if required Making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks Diving deep into issues and implementing solutions independently Identifying and reporting tooling bugs and suggesting improvements A day in the life We are looking for a ML Data Associate (MLDA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech, text, audio, video data. Your ability to concentrate, multi-task and your high attention to detail helps you deliver high-quality work as well as maintaining strict confidentiality and follow all applicable Amazon policies for securing confidential information. You will be a part of a diverse team with the shared vision of improving customers’ lives with practical, useful generative AI innovations. An inner drive, individuality, and a creative mind are extremely beneficial. Basic Qualifications Bachelor’s degree in a relevant field or equivalent professional experience 2+ yrs of experience working with written language data, including experience with annotation, and other forms of data markup. Strong research skills to gather relevant information, understand complex topics, and synthesize multiple resources; understanding of basic academic integrity, i.e. plagiarism. Excellent attention to details and ability to focus for a long period of time Ability to effectively write and evaluate diverse subject matter across various domains* Ability to adapt writing style to suit various style guidelines and customers. Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy Preferred Qualifications Strong proficiency in English. Candidate must demonstrate excellent writing, reading, and comprehension skills (C1 level in the Common European Framework CEFR scale). Experience with creating complex data for LLM training and evaluation Comfortable with high-school level STEM* Strong understanding of U.S.-based culture, society, and norms. Familiarity with common markup languages such as HTML, XML, Markdown Familiarity with common standard text formats such as JSON, CSV, RTF Working knowledge of Python or another scripting language Familiarity with regular expressions syntax Familiarity with Large Language Models Comfort in annotation work that may include sensitive content Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - ADCI MAA 12 SEZ Job ID: A3027635

Description Amazon is looking for an AI Content Expert II to help with annotations, content generation, and data analysis. As part of the Data Team, you will be responsible for delivering high-quality training data to improve and expand AGI's Large Language Models' (LLMs) capabilities. Key job responsibilities As an AI Content Expert, you will be responsible for creating training data that are complex in nature and will require you to make informed and high judgement decisions in each case. You will be working closely with scientists and engineers to review and update guidelines, identify tooling improvement opportunities, and engage in conversations regarding the quality of data. Creating and annotating high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content Writing grammatically correct texts in different styles with various degrees of creativity, stricly adhering to provided guidelines Performing audits and quality checks of tasks completed by other specialists, if required Making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks Diving deep into issues and implementing solutions independently Identifying and reporting tooling bugs and suggesting improvements A day in the life We are looking for a ML Data Associate (MLDA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech, text, audio, video data. Your ability to concentrate, multi-task and your high attention to detail helps you deliver high-quality work as well as maintaining strict confidentiality and follow all applicable Amazon policies for securing confidential information. You will be a part of a diverse team with the shared vision of improving customers’ lives with practical, useful generative AI innovations. An inner drive, individuality, and a creative mind are extremely beneficial. Basic Qualifications Bachelor’s degree in a relevant field or equivalent professional experience 2+ yrs of experience working with written language data, including experience with annotation, and other forms of data markup. Strong research skills to gather relevant information, understand complex topics, and synthesize multiple resources; understanding of basic academic integrity, i.e. plagiarism. Excellent attention to details and ability to focus for a long period of time Ability to effectively write and evaluate diverse subject matter across various domains* Ability to adapt writing style to suit various style guidelines and customers. Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy Preferred Qualifications Strong proficiency in English. Candidate must demonstrate excellent writing, reading, and comprehension skills (C1 level in the Common European Framework CEFR scale). Experience with creating complex data for LLM training and evaluation Strong understanding of U.S.-based culture, society, and norms. Comfortable with high-school level STEM* Familiarity with common markup languages such as HTML, XML, Markdown Familiarity with common standard text formats such as JSON, CSV, RTF Working knowledge of Python or another scripting language Familiarity with regular expressions syntax Familiarity with Large Language Models Comfort in annotation work that may include sensitive content Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - ADCI MAA 12 SEZ Job ID: A3027634

Selected Intern's Day-to-Day Responsibilities Work actively on computer vision and deep learning applications Work on challenging problem statements to fine-tune models with huge datasets Work on improving model accuracy and precision for CCTV cameras Compare the accuracy and performance of different CV models for a particular task Understand and work with Vision-Language Models (VLMs) Perform image annotation tasks to enhance dataset quality About Company: Faclon Labs is a Mumbai-headquartered deep-tech IoT company founded by IIT-Bombay alumni. Over the years, we have evolved into a one-stop and highly relevant IoT & AI company to drive digital transformation and Industry 4.0 among enterprises. Having a focus on deep technologies and continuous innovations, Faclon has become one of the leading companies in the IoT space with an aggressive portfolio of customers in India and overseas.

At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI. What We Do The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe. About The Role If you're a professional who works with AI Data Annotation and friendly user of LLMs, Mindrift offers a unique opportunity to apply your editing, annotating, fact-checking and creative skills to an AI training project. This is a freelance role for a project, and your typical tasks may include: Conduct high-quality web searches to verify facts, gather supporting data, and cross-check AI responses. Perform fact-checking and intent verification to ensure AI responses align with the user's goals. Carefully review and flag any inaccuracies, inconsistencies, or irrelevant answers. Provide structured feedback on AI-generated content to help improve model performance. Work effectively with large language models (LLMs), understanding their capabilities and limitations, and applying best practices when interacting with them Prompt generation with a purpose to receive the best quality result of LLMs How To Get Started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you'll help shape the future of AI while ensuring technology benefits everyone. Requirements You are currently enrolled in or completed a Bachelor's degree or higher You have professional and/or educational experience in data annotation, demonstrate a deeper-than-user-level interest in AI, and possess intellectual breadth and curiosity You are skilled in web searching, fact-checking, intent-checking, able to work with LLMs and have great attention to detail Your level of English is upper-intermediate (B2) or above You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge Benefits Why this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments Work on advanced AI projects and gain valuable experience that enhances your portfolio Influence how future AI models understand and communicate in your field of expertise

At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI. What We Do The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe. About The Role If you're a professional who works with AI Data Annotation and friendly user of LLMs, Mindrift offers a unique opportunity to apply your editing, annotating, fact-checking and creative skills to an AI training project. This is a freelance role for a project, and your typical tasks may include: Conduct high-quality web searches to verify facts, gather supporting data, and cross-check AI responses. Perform fact-checking and intent verification to ensure AI responses align with the user's goals. Carefully review and flag any inaccuracies, inconsistencies, or irrelevant answers. Provide structured feedback on AI-generated content to help improve model performance. Work effectively with large language models (LLMs), understanding their capabilities and limitations, and applying best practices when interacting with them Prompt generation with a purpose to receive the best quality result of LLMs How To Get Started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you'll help shape the future of AI while ensuring technology benefits everyone. Requirements You are currently enrolled in or completed a Bachelor's degree or higher You have professional and/or educational experience in data annotation, demonstrate a deeper-than-user-level interest in AI, and possess intellectual breadth and curiosity You are skilled in web searching, fact-checking, intent-checking, able to work with LLMs and have great attention to detail Your level of English is upper-intermediate (B2) or above You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge Benefits Why this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments Work on advanced AI projects and gain valuable experience that enhances your portfolio Influence how future AI models understand and communicate in your field of expertise

At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI. What We Do The Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe. About The Role If you're a professional who works with AI Data Annotation and friendly user of LLMs, Mindrift offers a unique opportunity to apply your editing, annotating, fact-checking and creative skills to an AI training project. This is a freelance role for a project, and your typical tasks may include: Conduct high-quality web searches to verify facts, gather supporting data, and cross-check AI responses. Perform fact-checking and intent verification to ensure AI responses align with the user's goals. Carefully review and flag any inaccuracies, inconsistencies, or irrelevant answers. Provide structured feedback on AI-generated content to help improve model performance. Work effectively with large language models (LLMs), understanding their capabilities and limitations, and applying best practices when interacting with them Prompt generation with a purpose to receive the best quality result of LLMs How To Get Started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you'll help shape the future of AI while ensuring technology benefits everyone. Requirements You are currently enrolled in or completed a Bachelor's degree or higher You have professional and/or educational experience in data annotation, demonstrate a deeper-than-user-level interest in AI, and possess intellectual breadth and curiosity You are skilled in web searching, fact-checking, intent-checking, able to work with LLMs and have great attention to detail Your level of English is upper-intermediate (B2) or above You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge Benefits Why this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments Work on advanced AI projects and gain valuable experience that enhances your portfolio Influence how future AI models understand and communicate in your field of expertise

Skill required: Marketing Operations - Digital Asset Management (DAM) Designation: Digital Content Management Specialist Qualifications: Any Graduation Years of Experience: 7 to 11 years About Accenture Accenture is a global professional services company with leading capabilities in digital, cloud and security.Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song— all powered by the world’s largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.Visit us at www.accenture.com What would you do? Help balance increased marketing complexity and diminishing marketing resources. Drive marketing performance with deep functional and technical expertise, while accelerating time-to-market and operating efficiencies at scale through Data and Technology, Next Generation Content Services, Digital Marketing Services & Customer Engagement and Media Growth Services. Role requires Digital Marketing Ads & Promotion creation/design Consists of management tasks and decisions surrounding the ingestion, annotation, cataloguing, storage, retrieval and distribution of digital assets What are we looking for? Problem solving and research skills Project management skills Ability to work under pressure and to work on multiple projects concurrently Excellent organizational and communication skills Effective verbal and written communication skills Demonstrates collaborative and professional work ethic Willingness to be flexible and respond to quickly changing priorities Experienced in one or more digital asset management technologies Ability to design systems for tagging images and cataloging taxonomy Knowledge of Adobe Creative Cloud software Knowledge of Capture One (for photo assets) In-depth knowledge of file formats (print, digital, and video) Basic knowledge of Search Engine Optimization (SEO) Organizational skills to develop a successful strategy that expands future digital content discovery and delivery to the CMS Basic knowledge of talent contracts and Rights Management Working knowledge of media usage rights terminology Familiarity with legal approval processes in the licensing industry Roles and Responsibilities: The DAM librarian manages internal company assets, provides skills in content and digital asset management (i.e.taxonomy,indexing,cataloging,archiving, metadata tagging,content management systems).As a function reporting to Creative Services, the Digital Asset Management (DAM) team strategically implements and manages the DAM tool which will house all final creative assets,including,but not limited to,graphic design elements,photography,packaging,catalog content,iconography,video,music,and content.This role will need to work with the users of the DAM system to support their use and navigation around the solution.The DAM Librarian will be the first point of contact for the users and be responsible for working collaboratively in order to understand their working processes with respect to metadata and taxonomy. This requires working closely with the other content teams,such as CMS, Platform Marketing, Regulatory Operations,Labeling,and Publishing,to ensure consistent metadata standards are used. In addition,the DAM Librarian is responsible for managing schemas and dictionaries within the DAM system.This position will influence the strategic set-up and business use of digital assets and unstructured content (i.e.,videos,images,etc).It will help establish process / user management standards,including best practice metadata, taxonomy, permissions and workflows that span the company’s global businesses. It will lead the alignment of taxonomy across company BUs and markets. It will provide support for user accounts, training and establish / track KPIs. It will be the functional steward for"single source of the truth" by making DAM the master resource for digital assets.Primary Responsibilities and Duties: Prepare a long-term plan for categorizing, indexing and archiving all content and information resources, whether they be generated in-house or derived from third-party agents Develop a comprehensive taxonomy for organizing information resources based on business goals and requirements from stakeholders Assess, recommend, and purchase corporate library development tools as required,and track new standards and methodologies Compile and maintain a detailed inventory of existing electronic and print marketing tactic resources,and identify knowledge gaps and make recommendations Properly select and annotate a large volume of media into the digital asset management system to facilitate retrieval and use in production Evaluate digital assets for archiving, research rights issues,and maintain quality control of archiving operations Support effective working relationship

About Entrupy Entrupy is a global technology company whose mission is to protect businesses, borders and consumers from transacting in counterfeit goods. Entrupy has developed a patented technology system which utilizes a combination of AI and computer vision to instantly identify and authenticate high value physical goods. Entrupy's solutions serve business customers including leading luxury brands, retailers, e-commerce marketplaces and online resellers in over 60 countries. Entrupy is growing quickly with team members based in the US, India, Japan and Brazil. Entrupy's solutions in market: Entrupy Luxury Authentication Entrupy Sneaker Authentication Entrupy Fingerprinting As we continue to build... We're seeking curious, growth minded thinkers to help shape our vision, structures and systems; playing a key-role as we launch into our ambitious future. If you're invigorated by our mission, values, and drive to change the world — we'd love to have you apply. About Entrupy Entrupy is a cutting-edge technology company focused on product authentication using AI and machine learning. As we expand into apparel authentication, we're building a world-class team to power our next phase of growth. Role Overview We are looking for a detail-oriented and fashion-savvy Apparel Tagging and Annotation Specialist to support our machine learning and knowledge systems teams. In this role, you will work closely with fashion experts and data teams to accurately tag and annotate apparel images and information across various brands, styles, and categories. Your work will directly contribute to training AI models and building scalable authentication tools. Reports to Apparel Manager Location Type: Onsite - Bangalore Contract Duration: 6 -12 months Start Date: July 15, 2025 Key Responsibilities Review and tag images of apparel items based on pre-defined criteria (e.g., brand, logo placement, graphics, hardware, stitching patterns, etc.) Annotate specific product features using our internal tools to support data collection and machine learning. Identify and log variations in design, material, or labeling across different SKUs and seasons. Ensure high quality and consistency of all annotations with strong attention to detail. Collaborate with fashion experts, knowledge analysts, and engineers to iterate on tagging frameworks Meet daily/weekly productivity and accuracy targets. Qualifications Strong interest or background in fashion/apparel – familiarity with luxury and contemporary brands is a plus. Ability to work independently and stay organized in a fast-paced environment. Excellent attention to detail and ability to follow complex tagging guidelines. Comfortable using annotation or labeling tools (experience with SaaS or internal platforms is a plus). Entrupy embraces a diversity of backgrounds and experiences and provides equal opportunity for all applicants and employees. We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better our work (and work environment) will be for everyone.

Position Overview We are a seed-funded startup on a mission to revolutionize credit intelligence with cutting-edge AI, human-validated data, and seamless workflows. Our founding team includes engineers from Apple, Amazon, and leading fintechs. With our platform live and early customers onboarded, we’re building out the engine that keeps our data fresh, accurate, and comprehensive. We’re looking for a Data Procurement & Operations Manager/Lead to own supplier sourcing, vendor relationships, report delivery, and the evolution of our in-house annotation and QC tooling. You’ll be the glue between business needs, external data partners, and our engineering team—ensuring every report meets our SLAs for coverage, quality, and turnaround. Key Responsibilities Vendor Sourcing & Onboarding: Identify, evaluate, and contract 5–8 high-value data providers (public filings, import export logs, alternative feeds). Define SLA agreements (throughput, accuracy, TAT) and ramp vendors to full capacity End-to-End Delivery Operations: Maintain the master delivery calendar and dashboards. Track vendor performance; drive corrective action on misses in quality or timeliness. Lead weekly ops stand-ups and monthly performance reviews with finance Process Design & Continuous Improvement: Document core workflows; run quarterly retrospectives to remove manual hand-offs. Partner with QAs and engineers to automate repeatable steps in our annotation platform. Own the backlog of tooling enhancements: auto-QC rules, reporting dashboards, user-training Cross-Functional Collaboration & Reporting: Serve as primary liaison between Data QA, Product, Engineering, and Customer Success. Produce weekly status reports on vendor pipeline, costs/unit, defect rate, and cycle time. Present ops health, risks, and improvement plans in leadership reviews Qualifications Bachelor’s or Master’s degree in Business, Engineering, Data Science, or related field 5–7 years in data procurement, vendor management, or operations—ideally in financial-data, supply chain data or annotation services Proven track record negotiating SLAs and managing third-party suppliers at scale Solid analytical chops: basic python and comfortable with SQL Experience defining processes, running retrospectives, and driving automation projects Excellent communicator who thrives in a fast-paced, cross-functional startup environment What We Offer Impact & Ownership: You’ll be foundational in scaling our data engine—directly shaping product quality and reliability. Competitive Package and Collaborative Culture Growth Path: Lead vendor strategy today; evolve into Head of Data as we expand.

Job Title: Senior Code Reviewer (Python) – LLM Data Training Employment Type: Contract · Remote Compensation: USD $15 – $22 per hour About OpenTrain AI OpenTrain AI assembles expert engineering teams that help top AI companies refine, test, and scale their models. We specialize in high-accuracy data labeling, quality assurance, and evaluation workflows—delivered entirely remotely. The Role We’re looking for a seasoned Python professional to audit evaluations of AI-generated code. You will review annotator assessments, verify code correctness and security, and provide concise feedback that directly improves large-language-model (LLM) performance. Key Responsibilities Examine annotator reviews of AI-produced Python solutions for instruction compliance, functional accuracy, and secure coding Re-run or unit-test snippets in Docker-based sandboxes to confirm “proof-of-work” results Identify and correct inaccuracies in annotator reasoning; deliver clear, constructive feedback Meet turnaround and quality targets within a rubric-driven workflow Collaborate asynchronously with OpenTrain AI leads to refine guidelines and address edge cases Required Qualifications 5–7 + years professional experience in Python development, QA, or formal code review Expert knowledge of modern Python (≤ 3.12), testing frameworks (pytest/unittest), and profiling/debugging tools Demonstrated secure-coding mindset (e.g., injection, deserialization, race conditions) Basic Docker proficiency (build, run, exec, multi-stage images, volume mounts) Comfortable executing and validating code in sandboxed/containerized environments Experience with structured QA or annotation workflows (checklists, rubric-based scoring) Excellent written English (B2 CEFR or higher) for clear, actionable feedback Reliable remote setup: modern hardware, high-speed internet, ability to meet milestone deadlines Preferred (Nice-to-Have) Hands-on work with LLM evaluation, RLHF, or model-alignment pipelines Familiarity with data-labeling or annotation platforms (e.g., Labelbox, Scale AI) Proven record of mentoring developers on code quality and security best practices What We Offer Competitive hourly rate paid promptly in USD Flexible remote schedule with milestone-based deliverables Chance to influence cutting-edge AI systems with your Python expertise Long-term project pipeline and opportunities for repeat engagements

Client Type: US Client Location: Remote The hourly rate is negotiable. About the Role We’re creating a new certification: Google AI Ecosystem Architect (Gemini & DeepMind) - Subject Matter Expert . This course is designed for technical learners who want to understand and apply the capabilities of Google’s Gemini models and DeepMind technologies to build powerful, multimodal AI applications. We’re looking for a Subject Matter Expert (SME) who can help shape this course from the ground up. You’ll work closely with a team of learning experience designers, writers, and other collaborators to ensure the course is technically accurate, industry-relevant, and instructionally sound. Responsibilities As the SME, you’ll partner with learning experience designers and content developers to: Translate real-world Gemini and DeepMind applications into accessible, hands-on learning for technical professionals. Guide the creation of labs and projects that allow learners to build pipelines for image-text fusion, deploy Gemini APIs, and experiment with DeepMind’s reinforcement learning libraries. Contribute technical depth across activities, from high-level course structure down to example code, diagrams, voiceover scripts, and data pipelines. Ensure all content reflects current, accurate usage of Google’s multimodal tools and services. Be available during U.S. business hours to support project milestones, reviews, and content feedback. This role is an excellent fit for professionals with deep experience in AI/ML, Google Cloud, and a strong familiarity with multimodal systems and the DeepMind ecosystem. Essential Tools & Platforms A successful SME in this role will demonstrate fluency and hands-on experience with the following: Google Cloud Platform (GCP) Vertex AI (particularly Gemini integration, model tuning, and multimodal deployment) Cloud Functions, Cloud Run (for inference endpoints) BigQuery and Cloud Storage (for handling large image-text datasets) AI Platform Notebooks or Colab Pro Google DeepMind Technologies JAX and Haiku (for neural network modeling and research-grade experimentation) DeepMind Control Suite or DeepMind Lab (for reinforcement learning demonstrations) RLax or TF-Agents (for building and modifying RL pipelines) AI/ML & Multimodal Tooling Gemini APIs and SDKs (image-text fusion, prompt engineering, output formatting) TensorFlow 2.x and PyTorch (for model interoperability) Label Studio, Cloud Vision API (for annotation and image-text preprocessing) Data Science & MLOps DVC or MLflow (for dataset and model versioning) Apache Beam or Dataflow (for processing multimodal input streams) TensorBoard or Weights & Biases (for visualization) Content Authoring & Collaboration GitHub or Cloud Source Repositories Google Docs, Sheets, Slides Screen recording tools like Loom or OBS Studio Required skills and experience: Demonstrated hands-on experience building, deploying, and maintaining sophisticated AI powered applications using Gemini APIs/SDKs within the Google Cloud ecosystem, especially in Firebase Studio and VS Code. Proficiency in designing and implementing agent-like application patterns, including multi-turn conversational flows, state management, and complex prompting strategies (e.g., Chain-of Thought, few-shot, zero-shot). Experience integrating Gemini with Google Cloud services (Firestore, Cloud Functions, App Hosting) and external APIs for robust, production-ready solutions. Proven ability to engineer applications that process, integrate, and generate content across multiple modalities (text, images, audio, video, code) using Gemini’s native multimodal capabilities. Skilled in building and orchestrating pipelines for multimodal data handling, synchronization, and complex interaction patterns within application logic. Experience designing and implementing production-grade RAG systems, including integration with vector databases (e.g., Pinecone, ChromaDB) and engineering data pipelines for indexing and retrieval. Ability to manage agent state, memory, and persistence for multi-turn and long-running interactions. Proficiency leveraging AI-assisted coding features in Firebase Studio (chat, inline code, command execution) and using App Prototyping agents or frameworks like Genkit for rapid prototyping and structuring agentic logic. Strong command of modern development workflows, including Git/GitHub, code reviews, and collaborative development practices. Experience designing scalable, fault-tolerant deployment architectures for multimodal and agentic AI applications using Firebase App Hosting, Cloud Run, or similar serverless/cloud platforms. Advanced MLOps skills, including monitoring, logging, alerting, and versioning for generative AI systems and agents. Deep understanding of security best practices: prompt injection mitigation (across modalities), secure API key management, authentication/authorization, and data privacy. Demonstrated ability to engineer for responsible AI, including bias detection, fairness, transparency, and implementation of safety mechanisms in agentic and multimodal applications. Experience addressing ethical challenges in the deployment and operation of advanced AI systems. Proven success designing, reviewing, and delivering advanced, project-based curriculum and hands-on labs for experienced software developers and engineers. Ability to translate complex engineering concepts (RAG, multimodal integration, agentic patterns, MLOps, security, responsible AI) into clear, actionable learning materials and real world projects. 5+ years of professional experience in AI-powered application development, with a focus on generative and multimodal AI. Strong programming skills in Python and JavaScript/TypeScript; experience with modern frameworks and cloud-native development. Bachelor’s or Master’s degree in Computer Science, Data Engineering, AI, or a related technical field. Ability to explain advanced technical concepts (e.g., fusion transformers, multimodal embeddings, RAG workflows) to learners in an accessible way. Strong programming experience in Python and experience deploying machine learning pipelines Ability to work independently, take ownership of deliverables, and collaborate closely with designers and project managers Preferred: Experience with Google DeepMind tools (JAX, Haiku, RLax, DeepMind Control Suite/Lab) and reinforcement learning pipelines. Familiarity with open data formats (Delta, Parquet, Iceberg) and scalable data engineering practices. Prior contributions to open-source AI projects or technical community engagement.

- Bachelor’s degree in a relevant field or equivalent professional experience - 2+ yrs of experience working with written language data, including experience with annotation, and other forms of data markup. - Strong research skills to gather relevant information, understand complex topics, and synthesize multiple resources; understanding of basic academic integrity, i.e. plagiarism. - Excellent attention to details and ability to focus for a long period of time - Ability to effectively write and evaluate diverse subject matter across various domains* - Ability to adapt writing style to suit various style guidelines and customers. - Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy Amazon is looking for an AI Content Expert II to help with annotations, content generation, and data analysis. As part of the Data Team, you will be responsible for delivering high-quality training data to improve and expand AGI's Large Language Models' (LLMs) capabilities. Note: This a fixed term contractual role Key job responsibilities As an AI Content Expert, you will be responsible for creating training data that are complex in nature and will require you to make informed and high judgement decisions in each case. You will be working closely with scientists and engineers to review and update guidelines, identify tooling improvement opportunities, and engage in conversations regarding the quality of data. - Creating and annotating high-quality complex training data in multiple modalities (text, image, video) on various topics, including technical or science-related content - Writing grammatically correct texts in different styles with various degrees of creativity, stricly adhering to provided guidelines - Performing audits and quality checks of tasks completed by other specialists, if required - Making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks - Diving deep into issues and implementing solutions independently - Identifying and reporting tooling bugs and suggesting improvements A day in the life We are looking for a ML Data Associate (MLDA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech, text, audio, video data. Your ability to concentrate, multi-task and your high attention to detail helps you deliver high-quality work as well as maintaining strict confidentiality and follow all applicable Amazon policies for securing confidential information. You will be a part of a diverse team with the shared vision of improving customers’ lives with practical, useful generative AI innovations. An inner drive, individuality, and a creative mind are extremely beneficial. Strong proficiency in English. Candidate must demonstrate excellent writing, reading, and comprehension skills (C1 level in the Common European Framework CEFR scale). Strong understanding of U.S.-based culture, society, and norms. Comfortable with high-school level STEM* Experience with creating complex data for LLM training and evaluation Familiarity with common markup languages such as HTML, XML, Markdown Familiarity with common standard text formats such as JSON, CSV, RTF Working knowledge of Python or another scripting language Familiarity with regular expressions syntax Familiarity with Large Language Models Comfort in annotation work that may include sensitive content Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

We are hiring a Code Reviewer with deep Python expertise to review evaluations completed by data annotators assessing AI-generated Python code responses. Your role is to ensure that annotators follow strict quality guidelines related to instruction-following, factual correctness, and code functionality. Responsibilities Review and audit annotator evaluations of AI-generated Python code. Assess if the Python code follows the prompt instructions, is functionally correct, and secure. Validate code snippets using proof-of-work methodology. Identify inaccuracies in annotator ratings or explanations. Provide constructive feedback to maintain high annotation standards. Work within Project Atlas guidelines for evaluation integrity and consistency. Required Qualifications 5–7+ years of experience in Python development, QA, or code review. Strong knowledge of Python syntax, debugging, edge cases, and testing. Comfortable using code execution environments and testing tools. Excellent written communication and documentation skills. Experience working with structured QA or annotation workflows. English proficiency at B2, C1, C2, or Native level. Preferred Qualifications Experience in AI training, LLM evaluation, or model alignment. Familiarity with annotation platforms. Exposure to RLHF (Reinforcement Learning from Human Feedback) pipelines. Why Join Us? Join a high-impact team working at the intersection of AI and software development. Your Python expertise will directly influence the accuracy, safety, and clarity of AI-generated code. This role offers remote flexibility, milestone-based delivery, and competitive compensation.

We're Hiring: Freelance Coding Specialists – AI Foundational Models (Remote | 40 hrs/week | Contract/Freelance) We’re looking for exceptional Freelance Coders/Software Engineers to contribute directly to the development of cutting-edge AI models. This isn’t just annotation work—you’ll be helping shape how AI understands and writes code .What You'll Do :Evaluate and refine AI-generated code through Reinforcement Learning with Human Feedback (RLHF) and Supervised Fine-Tuning (SFT) .Craft and test complex prompts, assess AI responses, and rewrite outputs for accuracy and clarity .Debug logic issues, identify improvement areas, and contribute across a range of code-heavy AI tasks .What You Bring :Fluent in at least one programming language (Python, JavaScript, C++, etc.) .3+ year of relevant work experience (excluding internships) .Strong CS fundamentals, or a Tier 1 educational/professional background .Excellent English communication skills .40+ hours/week availability, with your own laptop and stable internet .Self-motivated, disciplined, and detail-oriented .Bonus Points For :Experience with code reviews or technical writing .Strong structured thinking and analytical mindset .Prior exposure to AI/ML (not mandatory if your coding is top-tier) .Why Join Us :Contribute directly to foundational AI systems used by millions .Work on meaningful, high-impact coding projects .Remote, flexible hours with global collaboration .Build AI domain expertise and career capital .Pay :Starts at $16.5/hr (40 hrs/week) .Up to $27.5/hr post-probation based on performance .Weekly payouts on approved work .

We’re hiring a Code Reviewer with deep Python expertise to review evaluations completed by data annotators assessing AI-generated Python code responses. Your role is to ensure that annotators follow strict quality guidelines related to instruction-following, factual correctness, and code functionality. Responsibilities · Review and audit annotator evaluations of AI-generated Python code. · Assess if the Python code follows the prompt instructions, is functionally correct, and secure. · Validate code snippets using proof-of-work methodology. · Identify inaccuracies in annotator ratings or explanations. · Provide constructive feedback to maintain high annotation standards. · Work within Project Atlas guidelines for evaluation integrity and consistency. Required Qualifications · 5–7+ years of experience in Python development, QA, or code review. · Strong knowledge of Python syntax, debugging, edge cases, and testing. · Comfortable using code execution environments and testing tools. · Excellent written communication and documentation skills. · Experience working with structured QA or annotation workflows. · English proficiency at B2, C1, C2, or Native level. Preferred Qualifications · Experience in AI training, LLM evaluation, or model alignment. · Familiarity with annotation platforms. · Exposure to RLHF (Reinforcement Learning from Human Feedback) pipelines.

Job Title: Engineering Manager ( Contributor Success Manager - CSM) Company : Scale AI / Outlier AI Location : Remote (Work from anywhere) About Us Outlier AI partners with the world’s most innovative companies to enhance their AI models through human feedback. We are seeking Subject Matter Experts across various domains to contribute their expertise in training generative AI models. Job Summary: The Contributor Manager role is a pivotal position focused on identifying roadblocks, proposing solutions for moving projects forward, and managing a squad of contributors for Managed Workforce Program to ensure the efficient execution of data annotation and quality assurance tasks to support assigned projects. This role entails engaging with team members, auditing tasks, providing feedback, conducting training sessions, and driving project performance. The Contributor Manager will have the authority to manage permissions, address concerns, engage in coaching conversations and recommendations regarding contributor performance management, and ensure the overall quality and productivity of the team. Structure Overview Contributors form squads; each squad holds from 30 to 50 contributors working on the same project and reporting to the same Contributor Manager. Each Contributor Manager is managing one or more projects, for which the Contributor Manager must manage the allocated contributors, manage third party and internal tools, and take action to achieve project milestones. Contributor Managers report to Senior Contributor Managers, who ensure that Contributor Managers understand and know the latest project goals and any project-specific instructions so they can provide feedback and the appropriate training to contributors. Senior Contributor Managers require support and quality training from Contributor Manager. This will guarantee the correct retraining for each contributor and maximize project quality. Key Responsibilities: 1. Project Knowledge and Communication: Coordinate and supervise project activities, ensuring that tasks are completed according to the project plan and within the specified timeline Provide regular project updates, address concerns, and manage expectations to ensure stakeholder satisfaction Create and develop accurate and up-to-date project documentation, including project plans, progress reports, change requests, and any other relevant project records 2. Quality Assurance and Task Management: Audit tasks completed by squad members, providing constructive feedback during daily training sessions and live working sessions. Achieve quality attainment for assigned projects by managing project output and providing feedback to contributors. Gather feedback from squad members to assess tasker sentiment and communicate with project delivery teams. Collaborate closely with project delivery teams to ensure high-quality work is being done 3. Training and Development: Conduct 1:1 enablement sessions every two weeks with squad members to review recent submissions and provide feedback. Coordinate with STOs to conduct training webinars and ensure alignment with project goals. Provide group feedback during daily team syncs on best practices and quality improvement strategies. Identify contributors for potential advancement opportunities and project leadership 4. Engagement and Support: Actively engage with the team through daily Zoom meetings, Slack, and email to provide ongoing support and guidance. Host daily working sessions for contributors to ask questions and foster collaboration. Clarify any doubts or issues raised by team members and relay project updates from STOs. Characteristics: Demonstrates a strong sense of responsibility by effectively prioritizing and managing contributions. Proficient in auditing tasks, providing constructive feedback, and driving quality improvement. Demonstrates initiative, curiosity, and a proactive approach to continuous improvement. Open to learning new skills and proposing innovative solutions to enhance team performance. Excellent organizational and communication skills with a collaborative mindset. Self-motivated, adaptable, and trustworthy with a focus on contributor retention and team dynamics. Qualifications: Proven experience in a project management or supervisory role in Engineering, preferably in data annotation or a related field. Familiarity with quality guidelines, auditing processes, and performance management. Ability to effectively use tools such as speed audit, rebirth, worker tags, and channel management. Strong understanding of project rules, instructions, and quality assurance standards. Proficient in accurately interpreting metrics and making informed decisions based on data analysis.

Freelance Opportunity: Native Telugu Linguist for Audio Annotation Project Remote | Part-Time | Contract-Based We are seeking native or near-native Telugu-speaking linguists for an ongoing audio annotation project . This is a flexible, remote, part-time opportunity ideal for individuals with a background in linguistics, language studies, or related fields—especially those experienced with transcription and audio tools. Key Responsibilities: Listen to and segment Telugu audio recordings based on speaker turns, timing, and linguistic cues Ensure high linguistic accuracy with attention to tone, context, and cultural nuance Annotate audio using tools such as Audacity, Adobe Audition , or similar platforms Evaluate audio clarity and correctness of language usage as part of quality checks Review transcripts for phonetic and linguistic accuracy; mark each entry as “accepted” or “rejected” Requirements: Native or near-native fluency in Telugu Educational background in Linguistics, Telugu Language, Philology , or related fields Experience with audio annotation/transcription tools (Audacity, Adobe Audition, etc.) Strong attention to detail and understanding of dialectal variations, pronunciation, and speech patterns Good internet connection and ability to work independently What We Offer: 100% remote work Flexible working hours Part-time, contract-based engagement Potential for long-term collaboration on similar projects Competitive compensation based on experience and availability Ideal Candidate: Able to dedicate time after regular office hours and during weekends Full-time freelancers are highly encouraged to apply To Apply, Please Submit: Your updated CV A brief summary of your relevant linguistic/audio annotation experience Your availability for a short introductory call Approximate daily hours you can dedicate to the project Email : sajid.ahmed@truelancer.com We’re excited to collaborate with talented Telugu linguists and bring language precision to the forefront of our work. Looking forward to your application!

We are seeking detail-oriented and reliable Data Annotators to join our team. The ideal candidate will be responsible for labeling, tagging, and annotating various types of data (text, images, videos, audio) to train AI/ML models. This role requires high attention to detail, consistency, and an ability to follow complex guidelines accurately. --- Key Responsibilities: Accurately annotate and label datasets (text, image, video, or audio) according to project-specific instructions. Identify and flag data quality issues and inconsistencies. Collaborate with project managers and quality analysts to ensure annotation standards are met. Meet daily or weekly productivity and accuracy targets. Participate in feedback sessions and implement changes based on QA reviews. Maintain confidentiality and data integrity at all times. --- Required Skills & Qualifications: Basic computer proficiency and typing speed. Strong attention to detail and concentration. Good communication and comprehension skills (English or regional language, depending on the project). Ability to follow instructions and guidelines precisely. Comfortable working with annotation tools or willingness to learn. Prior experience in data annotation is a plus, but not mandatory. --- Preferred Qualifications: Bachelor's degree or currently pursuing (any stream). Knowledge of AI/ML or data labeling concepts is an advantage. Familiarity with annotation platforms like Labelbox, CVAT, or VGG Image Annotator is a bonus. --- Working Conditions: [Include working hours, remote/onsite details, shift timings if applicable] A comfortable work environment with scope for learning AI/ML-related work. Training will be provided before starting the live project. --- Benefits: Training & mentorship provided Flexible work hours (for remote roles) Performance-based incentives Certificate of experience upon project completion

Role Overview We are looking for a dynamic and driven Sales / Business Development Manager – AI Data Services to lead client acquisition and revenue growth for our rapidly expanding AI data vertical. This role involves identifying and engaging with potential clients globally, understanding their AI training data needs, and offering tailored data collection, annotation, and validation solutions across modalities like speech, text, video, and image. You’ll work closely with cross-functional teams (project, tech, and QA) to ensure smooth onboarding and successful project delivery while deepening client relationships. Key Responsibilities Identify, target, and acquire new clients in AI, ML, SaaS, and Tech sectors globally Pitch company AI data capabilities for multilingual data collection, annotation, and validation services Build strong relationships with decision-makers – including Heads of Data, Product Managers, and AI Teams Work with internal teams to create customized proposals, pricing, and execution plans Manage the sales pipeline, forecast revenue, and maintain CRM hygiene Represent the company in client meetings, calls, demos, and industry forums Ensure smooth handoff from sales to project execution and support during delivery phases Stay updated with AI trends, use cases, and data demands across industries Preferred Qualifications 2–6 years of experience in business development and have experience onbaording Clients for AI Data Services Strong understanding of AI model development lifecycle and the role of training data Proven ability to drive and close international deals across geographies Excellent communication, negotiation, and relationship-building skills Prior experience in selling services or project-based solutions Comfortable working in a fast-paced, performance-driven environment Good to Have Familiarity with data services like speech collection, annotation, labeling, or transcription Exposure to working with startups, MLOps platforms, or data-focused product companies Network or contacts in the AI/ML ecosystem (startups, enterprise clients, or consulting firms) Multilingual skills and global market exposure Skills: negotiation,relationship building,business development,data collection,ai,multilingual data collection,data validation,sales pipeline management,data annotation,sales,client acquisition,ai data services,crm maintenance