• Review, label, classify, and validate data according to project guidelines.
• Ensure accuracy, consistency, and quality across assigned tasks.
• Identify edge cases, discrepancies, and annotation issues, escalating them when appropriate.
• Perform quality checks and provide clear, constructive feedback.
• Meet productivity and quality targets while working independently in a remote environment.

• Must be currently based in the United States. Applications from candidates outside the US will not be considered.
• Strong English reading, writing, and comprehension skills.
• Excellent attention to detail and analytical abilities.
• Ability to interpret guidelines and apply them consistently.
• Good communication and collaboration skills.
• Self-motivated with the ability to work independently.
• Desktop or laptop with a reliable internet connection.

• Prior experience in data annotation, content review, quality assurance, or similar work is preferred.
• Familiarity with AI or machine learning data projects is a plus.
• Basic proficiency with Google Workspace or Microsoft Office.
• Strong problem-solving skills and the ability to make consistent, objective decisions.

• Candidate Location: United States only.
• Commitment Required: At least 4 hours per day and a total of 40 hours per week with 4 hours of overlap with PST.
• Engagement Type: Contractor assignment / Freelancer (no medical or paid leave).
• Duration of Contract: 3–4 weeks.
• Time Zone Requirement: This role will require some overlap with UTC-8:00 (America/Los_Angeles) for 4 hours per day.

• Shortlisted candidates will be sent automated analytical challenges.
• Once you clear them, you are ready to go!

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems. Turing supports customers in two ways: first, by accelerating frontier research with high-quality data, advanced training pipelines, plus top AI researchers who specialize in coding, reasoning, STEM, multilinguality, multimodality, and agents; and second, by applying that expertise to help enterprises transform AI from proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.