You will perform audio editing and production tasks using Audacity, including trimming, mixing, and noise reduction. Additionally, you will record your screen to demonstrate and document workflows to help improve AI systems.
You will perform architectural design and BIM tasks using Blender Bonsai while documenting workflows through screen recordings. Your work will directly contribute to improving AI systems' understanding of architectural and BIM processes.
Audit AI model responses to sensitive chemical safety queries by classifying requests and ranking model outputs for accuracy and safety. Develop training content and evaluate AI performance to ensure model integrity and reliability across diverse chemical safety scenarios.
Develop expert-level technical questions and evaluation rubrics to assess and improve the reasoning capabilities of frontier AI models. Evaluate AI-generated content for accuracy, logical consistency, and technical rigor while critiquing peer rubrics for quality assurance.
You will perform professional image editing and graphic design tasks using GIMP while documenting your workflows through screen recordings. Your work will directly contribute to the improvement and evaluation of AI systems by providing high-quality creative data.
Evaluate and assess AI-generated and human-edited video content for technical accuracy, pacing, and adherence to professional production standards. Provide structured feedback and identify editing defects to improve the quality of AI training data.
Develop and refine AI training content by creating prompts and evaluating model responses for accuracy and safety. Ensure model integrity by testing for biases and potential risks across sensitive explosives and energetic materials topics.
You will use CATIA to create and edit 3D CAD models, mechanical parts, and assemblies while documenting your design workflows. Additionally, you will review technical tasks to provide feedback that helps improve AI model understanding of engineering processes.
Perform rigorous validation of marine geology and sedimentology reference answers to ensure technical accuracy for AI training. Evaluate AI-generated outputs regarding lithology, sedimentary structures, and core sampling protocols while providing detailed feedback.
The role involves reviewing and validating AI-generated responses for complex firearm and toolmark examination scenarios to ensure accuracy. You will provide feedback and document recommendations to improve AI model performance based on forensic laboratory standards.
Provide high-quality images, accurate labels, and contextual descriptions to support the training of AI systems. Collaborate with project coordinators to ensure deliverables meet project guidelines and deadlines.
Design and implement advanced methodologies for evaluating AI system safety, including red teaming and adversarial testing. Collaborate with stakeholders to translate security findings into actionable improvements for model robustness.
The Canva Specialist will create and document realistic design tasks to train AI models on visual design workflows. Responsibilities include preparing the work environment, recording task execution, and ensuring high-quality submissions.
Create realistic and challenging AWS-based tasks and document them clearly within the SuperAnnotate platform. Record yourself executing these cloud workflows to provide high-quality training data for AI models.
Evaluate and refine AI-generated responses for technical accuracy, logical soundness, and clarity across various civil engineering topics. Challenge language models with realistic engineering scenarios and provide structured feedback to improve model performance and safety.
Create challenging legal and compliance scenarios, detailed evaluation rubrics, reference analyses, and gold-standard examples for AI training. Evaluate AI-generated responses and peer rubrics for accuracy, completeness, reasoning quality, relevant risks, and professional rigor.
Evaluate and refine AI-generated responses for technical accuracy, logical soundness, and completeness in chemical engineering topics. Challenge language models with complex engineering scenarios and provide structured feedback on factual errors, safety considerations, and reasoning.
Review and evaluate AI-generated physics responses for accuracy, clarity, reasoning quality, and adherence to prompts; identify errors and fact-check physics content. Create high-quality prompts, explanations, and model solutions, and compare and rank responses to improve AI performance and reliability.
You will own the end-to-end delivery of coding data pipelines used to train frontier AI models. This involves coordinating across teams to define quality standards, drive workflow automation, and optimize pipeline performance metrics.
You will architect and scale distributed systems and platforms to support large-scale model training, inference, and agent execution. This role involves leading critical engineering initiatives and defining technical standards to improve research velocity and model performance.
Review and analyze inpatient medical records to ensure accurate ICD-10 coding and validate MS-DRG assignments. Evaluate AI-generated clinical notes against real-world documentation standards to improve model performance.
Annotate and review clinical content and inpatient documentation to ensure accuracy and clinical soundness. Evaluate AI-generated outputs for clinical safety and appropriateness across various inpatient care scenarios.
Build realistic transaction environments and design multi-step tasks involving valuation, financial modeling, and sell-side advisory. Utilize agentic AI tools to develop and review deal materials such as CIMs, pitch books, and valuation models.
Develop natural, human-enacted customer service conversations to train AI agents. Evaluate and rank AI responses to ensure accuracy, fluency, and contextual relevance.
Design realistic, multi-step finance and accounting tasks that include objective grading criteria for AI training purposes. Ensure tasks are based on real-world workflows such as financial reporting, audit procedures, and reconciliations.
The specialist will reconstruct and enhance Microsoft PowerPoint presentations to improve clarity, visual impact, and narrative flow. Additionally, they will contribute domain-specific insights to help train and evaluate next-generation AI systems.
The Finance Specialist will reconstruct and enhance financial PowerPoint presentations to effectively communicate complex data and insights. They will also review and refine content to ensure accuracy, readability, and alignment with investor-ready standards.
The developer will solve and validate Rust backend problems, including API design, concurrency, and performance optimization. They are also responsible for preparing Rust crate workspaces, test fixtures, and containerized environments for AI-training projects.
You will test AI agents by performing real-world errands such as shopping, booking, and bill payments while documenting the process. You are responsible for screen recording each attempt and providing detailed feedback on agent performance and satisfaction.
Develop and validate machine learning models, training pipelines, and inference systems. Implement model components, data pipelines, and numerical methods while ensuring reproducible programmatic workflows.
Design multi-step business operations tasks and define objective grading criteria for AI evaluation. Create supporting materials such as spreadsheets and process documentation to ensure tasks are realistic and measurable.
Create technically rigorous problems involving biomedical signals and develop clear reference solutions using scientific computing environments. You will apply expertise in signal processing and machine learning to evaluate and improve next-generation AI systems.
Solve complex scientific, mathematical, or technical problems within your domain of expertise. Review AI-generated solutions to identify factual errors, incorrect reasoning, and technical mistakes.
Develop challenging financial tasks and scoring rubrics to evaluate AI-generated financial analyses for accuracy and methodology. Identify material errors in financial logic and support AI training through high-quality reference content and expert critiques.
Review medical records and clinical documentation to support the training and improvement of next-generation AI systems. Ensure clinical information is accurate, consistent, and supported by medical records while identifying potential errors in dosing or medication interactions.
Create and solve technically rigorous scientific problems while developing reproducible Python-based analyses and models. Review scientific solutions and code to ensure correctness, clarity, and completeness.
You will apply your financial expertise to provide feedback on planning scenarios and evaluate investment strategies to help train AI systems. You will also collaborate with other financial experts to discuss approaches and ensure the accuracy of financial content.
Review and analyze complex insurance claims, including auto liability, property damage, and contents valuation, using various forms of evidence. Draft professional determination reports and provide insights to improve the accuracy of AI insurance claims processing systems.
Evaluate and annotate complex financial materials and transaction documents to enrich AI learning datasets. Draft, review, and edit project deliverables such as pitchbooks and valuation models while providing feedback on AI-generated content.
The expert will solve and validate aerodynamic and fluid-dynamics problems by creating computational models and running simulations. They will use Python to automate preprocessing, simulation execution, and postprocessing workflows.
The expert will create, solve, and validate complex mechanical engineering tasks involving structural, thermal, and multiphysics simulations. This role requires translating physical requirements into computational models using Python and advanced engineering software.
Solve self-contained coding, logic, and technical reasoning challenges to support AI training. Analyze unfamiliar problems and translate requirements into reproducible, implementable software solutions.
You will review and analyze simulated retail scenarios to ensure the accuracy and authenticity of AI model outputs. Additionally, you will provide expert insights on industry standards, compliance, and operational workflows to improve AI reasoning.
The specialist will review and evaluate AI-generated answers regarding VA health care eligibility and enrollment against established rubrics. They will also provide clear written feedback to the project team to ensure accuracy and compliance with VA guidance.
The role involves solving and validating advanced mathematical problems by translating them into precise, executable Python workflows. Experts will implement numerical experiments, automate calculations, and ensure the mathematical validity of computational results.
Develop and validate machine learning models, training pipelines, and inference systems while optimizing performance. Construct reproducible programmatic workflows and resolve complex numerical or system-level engineering challenges.
The expert will solve and validate complex mechanical engineering problems involving design, simulation, and physical modeling. They are responsible for translating engineering requirements into computational models and utilizing coding agents to perform technical analysis.
Analyze, annotate, and label clinical dental data to support the development and training of AI models. Evaluate AI model outputs for clinical accuracy, relevance, and workflow realism while collaborating with cross-functional teams.
The practitioner will evaluate and refine interactive learning materials and assessments to ensure pedagogical accuracy and learner engagement. They will also provide expert feedback on educational content and contribute insights to improve AI-driven educational tools.
The role involves mapping analytic scenarios to a taxonomy and authoring detailed cases to train next-generation AI systems. You will evaluate model responses for accuracy and utility while documenting edge cases and providing feedback for iterative improvement.
Design and execute statistical analyses while developing and validating machine learning models to improve AI system performance. Provide expert-level feedback on model outputs, identify methodological flaws, and document findings with high precision.
You will execute digital workflows using AI tools to complete tasks and evaluate model performance. Additionally, you will document your process through screenshots and provide structured feedback to improve AI accuracy.
You will map cyber threat intelligence cases to established taxonomies and evaluate AI-generated threat responses for accuracy and utility. Additionally, you will document challenging edge cases and provide feedback to improve AI threat assessment capabilities.
Create technically rigorous hardware engineering problems based on industry scenarios and develop clear reference solutions. Utilize engineering software and tools to validate results and ensure work can be independently verified.
You will provide expert feedback on manufacturing processes and refine AI-generated content to improve model accuracy. Additionally, you will develop and validate rubrics to evaluate the efficiency and precision of manufacturing workflows.
Analyze and evaluate AI-generated psychological content for accuracy, ethics, and clinical relevance. Collaborate with multidisciplinary teams to integrate psychological frameworks into AI training processes.
The expert will create, solve, and validate complex mechanical engineering tasks involving computational modeling and simulation. They are responsible for translating physical requirements into analytical models and utilizing coding agents to execute engineering workflows.
Design and implement application fixtures with embedded security vulnerabilities to train and assess AI systems. Collaborate on agent-based security architecture and contribute to the continuous improvement of the evaluation pipeline.
You will build and scale full-stack applications using React, Node.js, and TypeScript while owning features from architecture to production. Additionally, you will develop reliable backend services and optimize databases to improve platform performance and developer experience.
Evaluate and refine interactive learning materials and assessments to ensure pedagogical accuracy and learner engagement. Provide expert feedback on educational content and contribute insights to improve AI-driven educational tools.
The role involves reviewing and validating simulated retail scenarios to ensure operational accuracy and authenticity for AI training. You will provide expert insights on industry standards, compliance, and best practices to improve AI model performance.
You will build reproducible reinforcement learning environments to test AI models on coding tasks like refactoring, bug fixing, and performance optimization. Additionally, you will implement deterministic verifiers to validate AI-generated solutions and document technical reasoning to improve training data quality.
You will build reproducible reinforcement learning environments to train AI models by creating coding tasks, bug fixes, and feature implementations. Additionally, you will refactor legacy code and implement deterministic verifiers to validate AI-generated solutions.
The IT Manager will provide strategic input on systems architecture, infrastructure optimization, and vendor management to support AI development. They will also contribute expertise in security compliance, risk mitigation, and team leadership to improve operational workflows.
Design and implement scalable software solutions while conducting detailed code reviews to ensure high-quality deliverables. Contribute programming expertise to help train next-generation AI systems through real-world input and documentation.
Evaluate AI-generated code for quality, correctness, and design while providing detailed technical feedback. Create challenging coding problems, reference solutions, and test cases to improve model performance.
Evaluate AI model outputs across statistics, machine learning, and quantitative problems. Create expert-level prompts and datasets while identifying flawed methodologies to provide structured feedback.
You will build reproducible data science environments and implement reference solutions for complex tasks. Additionally, you will develop evaluation criteria to test coding agents and refine tasks based on their performance.
You will test AI agents by running real-life errands such as bookings, shopping, and email follow-ups while screen recording the process. You are responsible for scoring the agent's performance and providing clear written feedback on the user experience.
Review and assess AI-generated quantitative research and trading strategy outputs focused on fixed income and rates markets. Provide detailed written feedback on model assumptions, statistical rigor, and methodological issues such as lookahead bias and overfitting.
Review medical records and inpatient documentation to provide high-quality input for training AI systems. Identify inconsistencies in clinical data and provide feedback to improve model performance and data quality.
Review medical records and clinical documentation to support the training and improvement of AI models. Ensure clinical information is accurate, consistent, and supported by medical records while providing feedback to the project team.
Evaluate and provide feedback on AI-generated trading strategies for various rates products to improve their accuracy and market viability. Collaborate with technology teams to refine trading logic and ensure AI recommendations align with real-world market practices.
Review and annotate short video and audio clips while assessing the accuracy of AI-generated descriptions. Maintain data integrity and provide clear written feedback to support process improvements and content moderation standards.
Review medical records and clinical documentation to provide high-quality input for training next-generation AI systems. Identify inconsistencies in clinical data and provide feedback to improve model performance and data quality.
The Registered Nurse will annotate and review clinical content and inpatient documentation to ensure accuracy and clinical soundness. They will also evaluate AI-generated outputs for clinical safety and appropriateness across various care scenarios.
You will serve as a forward-deployed research partner embedded in enterprise AI systems to identify failure modes and improve performance. Responsibilities include designing high-signal datasets, running experimental loops, and developing robust agentic workflows.
You will develop, modify, and debug front-end and back-end application components while contributing to an AI training project. Responsibilities include tracing data across systems, diagnosing technical failures, and reviewing AI-generated code for performance and security.
Design and build small-scale game projects and interactive scenes to serve as assessment tasks for AI systems. Integrate gameplay bugs and feature challenges while drafting clear instructions and success criteria for evaluation.
The graphic designer will create high-quality visual assets and digital illustrations to help train next-generation AI systems. They will also collaborate with stakeholders to refine design outputs through iterative feedback cycles.
Review and assess AI responses to business analysis scenarios while ensuring data privacy and quality standards are met. Collaborate with research teams to develop evaluation frameworks and validate data consistency.
You will contribute to AI training by modeling real-world equity research, analyzing earnings reports, and synthesizing peer benchmarking insights. Additionally, you will produce high-quality research summaries and articulate investment theses based on deep sector expertise.
Create challenging mobile coding tasks and reinforcement learning environments to train AI models. Define problem parameters, build reproducible environments, and develop deterministic verifiers for code solutions.
You will test 2D and creative applications using real-world workflows to identify bugs, usability issues, and inconsistencies. Additionally, you will create and execute test cases while documenting clear feedback on application functionality and user experience.
The analyst will participate in expert interviews to provide insights into sell-side research methodologies and evaluate AI-powered tools for financial analysis. They will also document feedback and collaborate with project coordinators to improve the accuracy and relevance of AI-generated financial content.
The role involves creating high-quality visual assets and digital illustrations to help train next-generation AI systems. You will also critique existing materials and collaborate with stakeholders to ensure design consistency and impact.
You will perform simulated contract negotiations and redlining exercises to train and evaluate AI models. Additionally, you will collaborate with product and research teams to create evaluation frameworks and refine best practices for AI-driven contract review solutions.
Review and evaluate curated collections of images to assess their aesthetic quality, composition, and creative value. Document and articulate detailed critiques to help train next-generation AI systems.
The specialist will perform realistic financial workflows using the Bloomberg Terminal to support the development of AI systems. They are responsible for documenting processes, identifying data inconsistencies, and providing high-quality financial analysis.
Evaluate Tamil audio clips for nativeness, fluency, and linguistic authenticity to support AI model training. Document assessments with clear feedback and collaborate with coordinators to ensure high-quality results.
You will create challenging coding tasks for AI systems to solve, including feature implementation and bug fixes. Additionally, you will implement deterministic verifiers to validate AI solutions and ensure high-quality model performance.
The specialist will perform network monitoring, alert investigation, and log analysis within the Security Onion platform to support AI model training. They are responsible for documenting workflows, creating realistic prompts, and evaluating task outputs to ensure high-quality data.
The attorney will perform simulated litigation tasks and review AI responses to improve the precision and legal judgment of AI models. They will also collaborate with research teams to develop evaluation frameworks and guidelines for AI-driven legal solutions.
You will contribute to the design and development of end-to-end fullstack systems and internal platform capabilities. You will also build maintainable backend services and high-quality frontend interfaces while collaborating with cross-functional teams.
Evaluate AI-generated content for accuracy, safety, and policy alignment regarding chemical, biological, radiological, and nuclear topics. Identify and flag unsafe or misuse-enabling content while creating gold-standard reference examples for responsible AI behavior.
The Head of Communications will own and execute the company's external communications and PR strategy across media, customers, and the AI ecosystem. Responsibilities include managing media relations, developing messaging for product launches, and positioning company leaders through strategic speaking and interview opportunities.
The Research Marketing Lead will own the end-to-end go-to-market strategy for technical research, benchmarks, and AI evaluations. They will partner with research teams to translate complex technical findings into high-impact narratives that drive adoption and industry engagement.
Evaluate and improve AI model outputs regarding financial reasoning, valuation, and investment analysis. Create expert-level prompts and provide domain feedback to refine model behavior and accuracy.
You will evaluate and annotate data sets to train AI systems while providing expert insights on child development and behavior. You will also collaborate with interdisciplinary teams to ensure psychological integrity and create guidelines for AI interactions.
Evaluate AI-generated code for correctness, quality, and design while creating challenging engineering problems and test cases. Review model reasoning on architecture and provide detailed technical feedback to improve performance.
Evaluate AI model responses to complex business strategy problems and provide detailed feedback to improve performance. Apply structured frameworks to assess reasoning quality and collaborate with the project team to refine guidelines.
Design and create realistic business scenarios and tasks to train next-generation AI systems. Evaluate AI-generated solutions and provide actionable feedback to improve model performance for business documentation.
You will create Reinforcement Learning Environments to test AI models on complex software engineering tasks using Model Context Protocol tools. Your work involves designing reproducible environments and golden reference solutions to measure AI performance in software development.
The role involves reviewing and contributing to datasets that model real-world equity research to train AI systems. You will analyze earnings reports, perform valuation analysis, and articulate investment theses based on deep sector expertise.
The Data Engineer will design, build, and maintain scalable data pipelines to ingest and process large-scale datasets across cloud environments. They will collaborate with AI researchers and engineering teams to support data-intensive applications and model development.
Design and implement realistic cloud infrastructure environments to evaluate AI model proficiency in systems design and troubleshooting. Develop deterministic validation tests and failure scenarios to rigorously test AI model responses and recovery strategies.
The QA Engineer will own testing activities across new features and bug fixes while collaborating with engineering teams to ensure product quality. They are responsible for designing manual test cases, executing automated tests, and documenting issues throughout the development lifecycle.
Lead the visual direction and execution of high-quality video and motion content across brand campaigns and product launches. Translate complex AI and software concepts into engaging, technical, and futuristic visual stories.
Create, modify, and validate detailed parametric CAD models in FreeCAD while applying GD&T and DFM principles. Conduct engineering QA reviews and develop technical documentation to ensure model accuracy and manufacturability.
You will provide expert feedback on manufacturing processes and refine AI-generated content for manufacturing workflows. Additionally, you will develop and validate rubrics to evaluate the accuracy and efficiency of manufacturing processes.
Create and modify detailed parametric 3D CAD models and engineering drawings for mechanical components and assemblies. Perform quality assurance and prepare technical documentation to support the training of AI systems.
The Director will build and scale the operational infrastructure by designing automation roadmaps and managing the internal Ops Platform. They will collaborate cross-functionally with Product, Engineering, and Finance to translate complex operational needs into technical requirements.
You will create challenging coding tasks and implement deterministic verifiers to help train next-generation AI systems. The role involves designing tasks for feature implementation and bug fixes to shape how models learn and reason.
Analyze complex mechanical assemblies to identify design constraints and formulate technical questions for AI training. Review AI-generated outputs for mechanical reasoning accuracy and document edge cases for project improvement.
Review inpatient clinical documentation to assess accuracy, completeness, and clinical appropriateness. Adjudicate discrepancies and provide well-reasoned judgments while identifying significant errors or omissions.
You will perform personal finance workflow tasks and provide expert written explanations on Canadian financial topics to train AI systems. Additionally, you will review AI-generated financial guidance against rubrics to ensure accuracy and quality.
Review and evaluate PCB CAM and Gerber files for manufacturability while performing detailed visual inspections and defect analysis. Collaborate with project leads to refine workflow processes and contribute to the development of AI training datasets.
Analyze written content and AI-generated responses to ensure accuracy, clarity, and adherence to guidelines. Provide constructive feedback and document findings systematically using evaluation tools.
The role involves interpreting complex technical drawings, CNC documentation, and construction plans to provide expert feedback for training AI systems. You will also conduct safety and regulatory reviews of building and fire plans while producing clear technical explanations for project deliverables.
Evaluate and disposition First Article Inspections for regulatory compliance while assessing cosmetic defects in manufacturing contexts. Conduct virtual surveys and analyze inspection data to provide expert feedback for AI model development.
The technician will interpret complex technical diagrams to diagnose equipment faults and analyze PLC logic to identify root causes of operational issues. They will also document detailed troubleshooting reports and provide expert commentary to assist in training next-generation AI systems.
Review and annotate videos of robotic systems and mechanical components to support AI training. Ensure technical accuracy of annotations and provide feedback on complex or ambiguous examples.
Review and annotate robotic system videos by providing feedback based on electrical and electronic system observations. Analyze complex electrical schematics and document technical anomalies to assist machine learning specialists.
Develop and evaluate complex psychiatric case studies to inform AI model training with culturally nuanced scenarios. Conduct thorough psychological assessments and produce precise documentation in both Tagalog and English.
Review and annotate video footage from robotic systems to identify visual features and anomalies for AI training. Collaborate with development teams to refine annotation protocols and maintain high-quality, consistent datasets.
The specialist will manage and review Salesforce workflows, including leads, contacts, and opportunities to support business processes. They will also create reports and dashboards while documenting steps to train AI systems.
You will design, build, and manage complex Airtable workflows to support AI model training and data organization. Additionally, you will document these processes and provide feedback to ensure they reflect realistic operational use cases.
Evaluate code patches generated by LLMs and provide detailed feedback with written justifications. Conduct peer reviews of work submitted by other subject-matter experts.
The role involves using AI assistant tools to complete and evaluate everyday digital tasks like scheduling and emailing. You will provide structured feedback and grade AI responses to improve model performance and accuracy.
The specialist will reconstruct and enhance data-driven presentations to ensure visual consistency and narrative impact. They will also interpret complex datasets to develop analytics reports that provide actionable insights for stakeholders.
Review, analyze, and enhance book manuscripts to improve clarity, narrative structure, and market alignment. Collaborate with stakeholders to provide actionable editorial feedback and contribute to the development of AI editorial guidelines.
Analyze and reconstruct technical presentation slides to enhance clarity and visual impact while documenting complex system architectures. Collaborate asynchronously to refine technical narratives and support AI training initiatives through high-quality deliverables.
The role involves participating in realistic one-on-one tutoring and educational conversations to train AI systems. You will simulate common teaching scenarios, provide constructive feedback, and adapt your communication style to meet various learner needs.
Review inpatient cases for clinical quality, documentation accuracy, and appropriate care while providing feedback to improve AI model training. Collaborate with the project team to clarify complex cases and maintain high-quality review standards.
The role involves providing expert insights on IT strategy, systems architecture, and infrastructure to help train AI systems. You will also review documentation, workflows, and security compliance practices to improve operational efficiency and AI development.
The specialist will play and record AAA games using in-house tools to capture high-quality data for AI training. They are responsible for organizing, annotating, and securely transferring these game sessions while maintaining clear communication with the remote team.
The specialist will complete and document real-world GitHub workflows to generate high-quality interaction data for AI system development. Responsibilities include managing repositories, performing version control tasks, and recording screen demonstrations of these workflows.
The Community Manager will respond to customer inquiries and resolve support tickets while de-escalating conflicts across various channels. They will also monitor community activity and collaborate with internal teams to ensure customer needs are met.
Annotate and label audio and video content while ensuring high accuracy and consistency across datasets. Collaborate with project leads to resolve queries and provide feedback on annotation processes to improve workflows.
Reconstruct and enhance executive-level business slides for sales and go-to-market contexts using Microsoft PowerPoint. Provide a detailed reasoning log for all design and content changes to support AI training and evaluation.
Lead the design and execution of CRISPR-based gene editing experiments and develop cloning strategies for novel constructs. Collaborate with interdisciplinary teams to translate experimental data into structured formats for AI model training.
Design realistic business scenarios and engage in structured conversations with LLMs to evaluate document-related deliverables. Document feedback and provide side-by-side preference data to improve AI model quality and accuracy.
You will complete and document realistic Google Analytics workflows to provide high-quality interaction data for AI system development. This involves recording your screen, creating detailed rubrics, and reviewing outputs for accuracy.
The Stripe Specialist will execute and document realistic payment and financial workflows within the Stripe platform to generate high-quality interaction data. This role involves recording screen sessions, creating detailed rubrics, and explaining Stripe features to support the development of AI systems.
You will complete realistic music production workflows in FL Studio and document the steps taken to support AI system development. This involves recording your screen, creating detailed rubrics, and evaluating task outputs for accuracy.
You will complete and document realistic educational workflows within Google Classroom to support the development of AI systems. This includes creating assignments, managing student data, and recording your screen to demonstrate these processes.
The role involves performing simulated contract negotiations and redlining exercises to train and evaluate AI models. You will collaborate with research teams to create evaluation frameworks and provide expert feedback to improve AI precision in legal tasks.
Review and annotate video footage of robotic arms performing tasks to ensure accurate grading based on established guidelines. Collaborate with trainers and contributors to maintain high-quality standards and provide feedback to improve annotation processes.
You will create challenging coding tasks for AI systems involving feature implementation and bug fixes. Additionally, you will implement deterministic verifiers to validate AI-generated solutions.
You will analyze, debug, and resolve software vulnerabilities while contributing to the training of next-generation AI systems. Additionally, you will perform security audits, penetration testing, and refactor legacy code to enhance system performance and security.
Design and tune PID and advanced controllers for deployment on physical systems like robotics or industrial hardware. Develop and validate plant models using first principles and implement control algorithms in Python.
Create, review, and refine detailed civil and structural BIM models and drawing sets while ensuring compliance with international engineering codes. Provide high-quality domain input to train and evaluate AI-powered engineering systems.
You will apply your technical expertise to train next-generation AI systems by providing high-quality, real-world input. The role involves building scalable services, performing security audits, and optimizing backend performance.
You will apply your software engineering expertise to train next-generation AI systems by providing high-quality, real-world input. Your work involves building scalable services, optimizing performance, and resolving complex software bugs.
You will create Reinforcement Learning Environments to test AI models on complex software engineering tasks like debugging and refactoring. Additionally, you will contribute expert-level code samples and validate peer-contributed technical submissions to improve AI training data quality.
The Virtual Assistant will manage day-to-day administrative tasks, team logistics, and operational documentation. They will also oversee gifting operations, vendor coordination, and expense tracking for the distributed team.
You will analyze, profile, and optimize GPU kernels to maximize computational throughput while collaborating with stakeholders to identify and resolve bottlenecks. Additionally, you will refactor C++ and CUDA codebases and implement shader logic using GLSL and WebGPU to ensure seamless pipeline integration.
Reconstruct and enhance business slides for product and engineering roadmaps to train AI systems. Document detailed logs justifying all design and content improvements made to the slides.
Evaluate and refine AI-generated responses to ensure accuracy, clarity, and alignment with business objectives. Author and enhance technical documentation, strategy reports, and market analyses while providing actionable feedback on AI performance.
Analyze and reconstruct business slides related to travel, hospitality, and culinary topics to improve data visualization and visual storytelling. Document all changes made and provide rationales for design decisions to support AI model training.
You will create Reinforcement Learning Environments to test AI models on complex software engineering problems using Model Context Protocol tools. Your tasks include fixing bugs, implementing features, and refactoring code to measure AI performance and reasoning capabilities.
The Strategic Project Lead will own end-to-end project execution for AI Lab customers, from pipeline scoping to delivery. They will align operations and domain experts while maintaining clear client communication and driving rapid project milestones.
Provide expert feedback on manufacturing processes and refine AI-generated content related to CAM and CNC workflows. Develop and validate detailed rubrics to evaluate the accuracy and efficiency of manufacturing processes.
The role involves reconstructing and enhancing business slides for operations and service delivery projects to train AI systems. You will improve data visualization, narrative flow, and factual accuracy while providing written logs to justify your design and content choices.
Design, implement, and optimize GPU-based software solutions using CUDA, WebGPU, or GLSL. Profile and fine-tune GPU kernels and shaders while developing host-side logic in C++.
Analyze, review, and enhance AI-generated technical content while creating and refining prompts to guide AI model performance. Conduct rubric-based assessments and draft technical documentation to support the training of next-generation AI systems.
You will create Reinforcement Learning Environments to test AI models on complex software engineering tasks using Model Context Protocol tools. Responsibilities include fixing bugs, refactoring code, and designing reproducible environments to measure AI performance.
Analyze and synthesize information from public records and lengthy documents to produce accurate, factual articles. Participate in iterative editorial reviews and maintain transparency by documenting research methods and citation trails.
Diagnose and resolve complex hardware, software, and networking issues while documenting solutions in a ticket management system. Contribute detailed process insights to enhance support workflows and provide high-quality input for AI training data.
The Supply Chain Manager will utilize ERP systems to support supply chain workflows, build demand forecasts, and develop supplier evaluation scorecards. Additionally, the role involves analyzing inventory levels and preparing actionable reports using Excel to support procurement decision-making.
The role involves designing and producing expert-level evaluation tasks to train AI systems by simulating real-world data entry and validation challenges. You will also curate complex datasets and author detailed grading rubrics to assess AI agent performance.
Analyze and interpret domain-specific charts and data visualizations to provide accurate, step-by-step reasoning. Design clear, objective, and unambiguous tasks that require multi-step quantitative analysis for AI training purposes.
Interpret complex financial and operational charts to draft objective reasoning questions for AI training. Collaborate remotely to ensure high-quality, unambiguous tasks that support the development and evaluation of AI models.
Interpret complex statistical visualizations and design objective, multi-step analytical tasks to train AI systems. Deliver precise, unambiguous answers with detailed written explanations using advanced data science terminology.
The role involves analyzing, debugging, and refactoring codebases across multiple programming languages to support AI model training. You will also develop coding tasks and provide actionable feedback to evaluate and improve AI performance.
Develop, modify, and debug front-end and back-end application components while implementing user-facing features and supporting services. Evaluate and improve code written in multiple programming languages and review AI-generated solutions for performance and security.
You will conduct comprehensive financial research and build detailed Excel-based valuation models to support AI training initiatives. Additionally, you will prepare and critique client-facing materials, ensuring methodological accuracy and strategic clarity.
Develop, implement, and refine features within open source codebases while resolving complex bugs and refactoring legacy code. Collaborate remotely with contributors to maintain documentation and deliver high-quality, scalable technical solutions.
Engage in realistic one-on-one career coaching conversations to help train next-generation AI systems. Provide practical guidance on career planning, job searches, and professional development while following project guidelines.
Audit and reconcile CRM and revenue systems to resolve operational inconsistencies, policy conflicts, and data inaccuracies. Draft operational prompts and document technical reasoning to support system optimization and sustainable governance.
Design and develop high-quality, accessible user interfaces while collaborating with cross-functional teams to translate requirements into functional solutions. You will champion frontend best practices, including component reusability and performance optimization, to ensure a seamless user experience.
You will work directly with leading AI labs and enterprises to define research goals and implement ML and evaluation pipelines. This role involves building large-scale data intelligence systems and developing agentic workflows for production environments.
Design, build, and maintain scalable big data pipelines and architectures to support robust data solutions. Collaborate with cross-functional teams to implement data integration, transformation, and processing solutions.
You will design, develop, and refine machine learning models while managing large datasets using MongoDB. Additionally, you will collaborate with cross-functional teams to evaluate model performance and document technical workflows.
The specialist will analyze case-based scenarios and review AI-generated mental health guidance to ensure clinical accuracy and sensitivity. They will also develop best practices for trauma-informed care and collaborate with cross-disciplinary teams to refine training data quality.
Review and annotate short video and audio clips to support AI training and evaluation objectives. Provide clear written feedback on AI-generated descriptions and ensure content labeling adheres to project guidelines.
Evaluate and compare AI-generated responses against writing prompts to ensure clarity, tone, and instructional value. Provide detailed rationales and analytical scores while collaborating asynchronously with project managers.
Assess and score AI-generated responses based on clarity, tone, and adherence to instructions. Document detailed rationales for evaluations and identify factual inaccuracies or constraints violations.
You will author precise, verifiable question-and-answer sets based on multi-part CAD assemblies to train AI systems. Additionally, you will analyze complex mechanical designs and collaborate asynchronously to refine technical content.
Review and analyze extensive business data sets to ensure accuracy, relevance, and compliance with PII and data privacy protocols. Provide detailed feedback and recommendations to inform and refine AI training processes.
You will design and ship fullstack features, including backend APIs, data pipelines, and React frontends while managing platform infrastructure. You will also collaborate with research and operations teams to build resilient, observable systems using AI-driven development workflows.
Develop and validate machine learning models, training pipelines, and inference systems while optimizing for performance and hardware utilization. Diagnose complex system-level failures and review AI-generated code to ensure correctness and engineering quality.
The specialist will review and refine Shopify-related analytical tasks to ensure they align with real-world platform workflows and data models. They will provide actionable feedback to improve the realism and completeness of AI training scenarios.
The Senior AI Trainer will review and annotate video footage of robotic arms to provide high-quality data for training AI systems. This involves precise timestamping, event segmentation, and collaborating with team members to ensure annotation consistency.
Design and implement realistic cloud infrastructure environments to evaluate AI model proficiency in systems design and troubleshooting. Develop deterministic validation tests and failure scenarios to rigorously test AI model responses and recovery strategies.
Evaluate and rate AI-generated technical outputs against quality criteria while identifying inaccurate or incomplete information. Design comprehensive test cases for functional and edge-case scenarios and document defects with precise reproduction steps.
Develop high-difficulty question-and-answer pairs that challenge AI models on interpretation, argument, and analytical reasoning within the humanities. Research and provide authoritative citations while testing and refining questions against AI models to ensure accuracy and clarity.
You will apply your physics expertise to solve advanced problems and provide rigorous, well-documented derivations to help train next-generation AI systems. The role involves producing technically precise solutions using LaTeX and computational tools while ensuring high standards of reproducibility.
The expert will design, analyze, and validate various electronic circuits including analog, digital, and RF systems. They are also responsible for reviewing AI-generated circuit solutions and developing automated verification workflows using Python and CLI-based tools.
Analyze complex computer systems and business processes to identify improvements while gathering and validating requirements from stakeholders. Collaborate with cross-functional teams to troubleshoot technical issues and contribute domain expertise to AI training data design.
You will analyze technical decisions and evaluate architectural proposals to provide expert-level feedback. Additionally, you will produce comprehensive technical documentation and develop automation testing strategies to optimize system performance.
You will evaluate and improve AI model outputs regarding financial reasoning, valuation, and investment scenarios. This involves creating expert-level prompts and providing domain feedback to refine model behavior.
Evaluate AI model responses for accuracy, depth, and reasoning quality while creating expert-level prompts and critiques. Apply academic rigor to identify errors and help define performance standards for AI systems.
Evaluate AI-generated content for quality, accuracy, and structure while providing detailed editorial feedback. Develop reference materials that establish high standards for AI-generated writing.
You will create Reinforcement Learning Environments to test AI models on complex software engineering tasks like debugging, refactoring, and performance optimization. Additionally, you will contribute expert-level code samples and validate peer-contributed technical submissions.
Capture high-quality, first-person video footage of everyday activities using a smartphone to train AI systems. Ensure all metadata is accurate while adhering to strict privacy, safety, and consent protocols.
The specialist will assess and refine CRM data models while designing compliance-constrained workflows for SaaS revenue processes. They will also diagnose data integrity gaps and contribute operational insights to train AI systems.
You will configure and optimize CRM systems and revenue-related tools to improve operational efficiency and data integrity. Additionally, you will establish workflows, resolve policy conflicts, and provide actionable reporting to support high-growth teams.
Analyze technical materials to produce well-structured developer and product documentation. Create and edit high-quality content while adhering to information architecture and docs-as-code standards.
Analyze product and design challenges to articulate decision-making rationales through structured written deliverables like design docs and research reports. Evaluate design systems, accessibility, and frontend architecture while providing expert commentary on project artifacts.
Design, develop, and refine machine learning models while managing large datasets using MongoDB. Collaborate with cross-functional teams to evaluate model performance and integrate efficient data pipelines.
You will design, implement, and manage highly available PostgreSQL database architectures within a cloud-native environment. Additionally, you will optimize database performance, automate maintenance tasks, and ensure disaster recovery readiness.
Evaluate AI model responses to complex business strategy problems and provide detailed feedback to improve performance. Apply structured consulting frameworks to assess reasoning quality and identify gaps in model outputs.
Evaluate AI model outputs across statistics, machine learning, and quantitative reasoning to ensure high-quality performance. Create expert-level prompts, datasets, and reference solutions while providing structured feedback to improve model capabilities.
You will evaluate and improve AI model outputs regarding financial reasoning, valuation, and investment analysis. This involves creating expert-level prompts, identifying errors in model responses, and providing domain feedback to shape model behavior.
Design and simulate high-quality multi-turn conversations between users and AI assistants to improve Large Language Models. Collaborate with peers to ensure logical flow, proper tool usage, and adherence to quality guidelines.
The specialist will manage CRM operations, pipeline visibility, and forecasting to support revenue growth. They will also build dashboards and analyze sales trends to provide actionable insights for leadership.
You will create Reinforcement Learning Environments to test AI models on complex software engineering problems using Model Context Protocol tools. Your tasks include fixing bugs, implementing features, refactoring code, and optimizing performance to ensure high-quality AI training.
You will create Reinforcement Learning Environments to test AI models on complex software engineering problems using Model Context Protocol tools. Tasks include fixing bugs, implementing features, refactoring code, and optimizing performance to ensure high-quality model training.
Design visually compelling graphics, layouts, and interfaces while creating UI/UX wireframes and prototypes using Figma. Collaborate in a remote environment to provide feedback on design iterations and contribute insights on user interaction best practices.
Deliver empathetic and efficient customer support while documenting interactions using CRM software. Contribute expert product knowledge to address queries and provide input to train AI systems in real-world contexts.
You will create reinforcement learning environments to test AI models by solving full-stack software problems. This involves writing code, troubleshooting bugs across the UI and API layers, and documenting technical decisions to improve AI training data.
Identify, engage, and close partnerships with companies to acquire operational data for AI training and evaluation. Manage the full sales pipeline from initial outbound prospecting to signed agreement and partner onboarding.
Design, develop, and maintain scalable backend systems using Java and Spring Boot while architecting robust microservices. Collaborate with the team to review technical specifications, optimize system performance, and document technical solutions.
Design realistic DevOps tasks based on production scenarios and write working reference solutions with validation steps. Review AI-generated output to identify failures and provide precise corrections with reasoning.
Develop and maintain high-quality front-end interfaces using React and React Native while collaborating with designers. Deliver tasks independently within a distributed team environment to meet project specifications.
You will create Reinforcement Learning Environments to test AI models by developing code samples, debugging, and building features. Additionally, you will document your technical reasoning and review peer-contributed code to ensure high-quality training data.
Design and implement cloud infrastructure environments to evaluate AI model proficiency in systems design and deployment. Develop deterministic validation tests and failure scenarios to ensure the reliability and accuracy of reinforcement learning environments.
Design, build, and maintain scalable data pipelines and storage solutions to support AI-driven products and research. Collaborate with cross-functional teams to ensure data quality, operational reliability, and efficient processing workflows.
The expert will provide feedback on manufacturing processes and refine AI-generated content related to CAM and CNC workflows. They are also responsible for developing and validating rubrics to evaluate the accuracy and efficiency of manufacturing processes.
Conduct comprehensive legal analysis and research to support project objectives and provide nuanced insights. Draft, review, and edit legal documents while ensuring content quality and accuracy through structured feedback.
Develop high-quality model responses and 'golden responses' for complex mathematics prompts to be used in AI training. Collaborate with a global team to refine mathematical content and improve project guidelines.
Support the full recruitment lifecycle by sourcing candidates via LinkedIn and portals, validating profiles, and coordinating interviews. Maintain recruitment trackers and assist with hiring operations for both IT and Non-IT requirements.
