The Market Curation Editor will act as the human judgment layer for an automated political prediction app, reviewing and refining system-generated markets for accuracy and clarity. Responsibilities include verifying election data against authoritative sources, ensuring policy compliance, and monitoring political events to capture missing market opportunities.
You will conduct head-to-head evaluations of AI assistants by performing real-world business tasks and documenting failure modes. You will produce clear, reproducible reports that highlight how these tools perform for small business owners compared to competitors.
You will act as the human judgment layer for an automated prediction market pipeline, reviewing and refining culture-related markets for accuracy and relevance. This involves verifying event details, ensuring policy compliance, and proactively identifying culturally significant moments missed by the system.
You will act as the human judgment layer for an automated sports prediction pipeline, reviewing and refining system-generated markets for accuracy and clarity. This involves verifying event details, applying league-specific settlement conventions, and monitoring for errors or missing events.
Audit AWS Trainium and NKI tasks to ensure technical accuracy, reproducibility, and rigorous evaluation criteria. Provide actionable feedback on hardware acceleration inefficiencies, kernel execution bugs, and logic errors.
Audit and evaluate GPU kernel tasks to ensure technical accuracy, solvability, and reproducibility within AI training workflows. Provide actionable feedback on memory allocation, execution bottlenecks, and parallel computing logic errors.
Audit AI-assisted developer workflow tasks to ensure they are technically accurate, realistic, and reproducible. Provide actionable feedback on IDE integration faults, coding inefficiencies, and logic errors within the training tasks.
Audit AWS Serverless and Infrastructure as Code tasks to ensure technical accuracy, solvability, and reproducibility for AI training. Provide actionable feedback on deployment pipeline failures, configuration bugs, and architecture logic errors.
Audit machine learning tasks to ensure technical accuracy, solvability, and reproducibility. Provide actionable feedback on data pipeline flaws, model training inefficiencies, and algorithmic logic errors.
Audit and evaluate AI training tasks to ensure technical accuracy, realism, and reproducibility in CVE and application security. Provide actionable feedback on security vulnerabilities, exploit execution, and mitigation logic errors.
Audit Kubernetes tasks to ensure technical accuracy, reproducibility, and rigor for AI training workflows. Provide actionable feedback on orchestration issues, configuration bugs, and logic errors within the tasks.
Audit software engineering tasks to ensure they are technically rigorous, accurate, and reproducible for AI training. Provide actionable feedback on codebase integration issues, test failures, and logic errors.
Provide native-level Latvian linguistic QA, data annotation, and validation to ensure AI outputs are natural and culturally accurate. Develop educational resources and feedback documentation to improve AI alignment with campaign expectations.
Provide native-level Lithuanian linguistic QA and data annotation to ensure AI outputs are natural and culturally accurate. Develop educational resources and feedback documentation to improve AI alignment with campaign expectations.
Provide native-level Macedonian linguistic QA and data annotation to ensure AI outputs are natural and culturally accurate. Develop educational resources and feedback documentation to improve AI alignment and task quality.
Provide native-level Māori language vetting, QA, and data annotation to ensure AI outputs are natural and culturally accurate. Develop educational resources and feedback documentation to improve AI alignment with campaign expectations.
Provide native-level Nepali language vetting, QA, and data annotation to ensure AI outputs are natural and culturally accurate. Develop educational resources and feedback documentation to improve AI alignment with campaign expectations.
Provide native-level Norwegian linguistic QA and data annotation to ensure AI outputs are natural and culturally accurate. Develop educational resources and feedback documentation to improve AI alignment with campaign expectations.
Provide native-level Polish language vetting and quality assurance for AI data projects to ensure natural and unbiased outputs. Develop educational resources and feedback documentation to align AI task outputs with campaign expectations.
Provide native-level Brazilian Portuguese linguistic vetting and quality assurance for AI data projects. Develop educational resources and feedback documentation to improve AI output alignment and cultural accuracy.
Provide native-level Punjabi linguistic vetting and quality assurance for AI data projects to ensure natural and unbiased outputs. Develop educational resources and feedback documentation to improve AI alignment with campaign expectations.
Provide native-level Serbian linguistic QA, data annotation, and validation to ensure AI outputs are natural and culturally accurate. Develop educational resources and feedback documentation to improve AI alignment with campaign expectations.
Provide native-level Amharic linguistic QA, data annotation, and validation to ensure AI outputs are natural and culturally accurate. Develop educational resources and feedback documentation to improve AI alignment with campaign expectations.
The contractor will provide linguistic QA and develop alignment resources for an AI data project. This includes reviewing and annotating AI outputs for accuracy and cultural context.
The role involves providing linguistic quality assurance and developing alignment resources for an AI data project. Responsibilities include reviewing and annotating AI outputs for accuracy and cultural context.
The role involves providing linguistic QA and developing alignment resources for an AI data project. Responsibilities include reviewing and annotating AI outputs for accuracy and cultural context.
The role involves providing linguistic quality assurance and developing alignment resources for an AI data project. Responsibilities include reviewing and annotating AI outputs for accuracy and cultural relevance.
The role involves providing linguistic QA and developing alignment resources for an AI data project. Responsibilities include reviewing and annotating AI outputs for accuracy and cultural context.
The role involves providing linguistic quality assurance and developing alignment resources for an AI data project. Responsibilities include reviewing and annotating AI outputs for accuracy and cultural context.
The contractor will provide linguistic QA and develop alignment resources for an AI data project. Responsibilities include reviewing and annotating AI outputs for accuracy and cultural context.
