Video Data QA Specialist

About Turing: 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. Role Overview We are looking for experienced Video Data QA Specialists to support the OpenAI Egocentric project. The selected professionals will be responsible for reviewing video annotations and performing quality assurance checks to ensure that the data meets project requirements and quality standards. Job Responsibilities Review and QA video annotations according to project-specific guidelines. Validate the accuracy, completeness, and consistency of annotated video data. Identify, document, and correct annotation issues. Assess whether videos and annotations meet the required quality standards. Maintain a high level of attention to detail across a large volume of video content. Provide clear feedback on recurring errors or unclear cases. Follow established workflows and meet strict project deadlines. Collaborate with the project team to resolve questions and improve annotation quality. Job Requirements At least 3 years of experience in data annotation projects . Previous experience with video-based data annotation or video QA is strongly preferred. Experience reviewing, validating, or auditing annotated datasets. Strong visual attention to detail and analytical skills. Ability to consistently apply detailed quality guidelines. Availability to work on weekends when required due to tight project timelines. Reliable internet connection and access to a suitable computer. Nice to have Qualification: Prior experience with data annotation or labeling projects Benefits Opportunity to work on cutting-edge AI projects. Competitive compensation. Flexible working hours and remote work environment. Application Process Shortlisted candidates will complete an assessment. Once the assessment is cleared, candidates can start.