Company: Turing

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. 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.

We are hiring US-based academic dermatologists to contribute senior clinical expertise to data curation for frontier AI models and labs. The work supports a longitudinal dermatology dataset used by AI developers, regulatory teams, and academic groups. This is the senior reviewer track of the project. You will lead clinical review on complex cases, contribute to the development of clinical evaluation frameworks, and serve as expert advisor for client teams reviewing AI model outputs. Main tasks listed: Lead senior-level clinical review on complex or ambiguous cases; Facilitate structured resolution of clinical disagreement among reviewers; Contribute to the development of clinical evaluation frameworks; Provide expert advisory hours to client teams reviewing AI model outputs. The listing says the work can involve sensitive or graphic content.

We are seeking Life Science experts to contribute advanced scientific expertise to data curation and evaluation for frontier AI models and labs. This senior reviewer role focuses on reviewing complex life science problems, developing evaluation frameworks, and advising client teams assessing AI-generated scientific outputs.

The Business Analyst works on a Computer-Using Agent (CUA) evaluation project designed to assess and improve how AI systems understand instructions, analyze information, reason through problems, and complete tasks in digital environments. The role involves reviewing AI-generated responses and actions, validating information through online research, assessing accuracy and task completion, identifying errors or gaps, and providing detailed annotations, ratings, and explanations Main tasks listed: Analyze, summarize, and structure complex written content clearly and accurately; Conduct online research to verify claims, sources, and supporting evidence; Solve analytical, logical reasoning, data interpretation, arithmetic, and puzzle-based questions; Create scenarios and questions to evaluate and improve large language model performance.

The Business Analyst works on a Computer-Using Agent (CUA) evaluation project designed to assess and improve how AI systems understand instructions, analyze information, reason through problems, and complete tasks in digital environments. The role involves reviewing AI-generated responses and actions, validating information through online research, assessing accuracy and task completion, identifying errors or gaps, and providing detailed annotations, ratings, and explanations Main tasks listed: Analyze, summarize, and structure complex written content clearly and accurately; Conduct online research to verify claims, sources, and supporting evidence; Solve analytical, logical reasoning, data interpretation, arithmetic, and puzzle-based questions; Create scenarios and questions to evaluate and improve large language model performance.

We are seeking experienced US-based Medical Doctors (MD) or international equivalent (MBBS, MBChB, Medical Diploma, etc.) to help evaluate and enhance large language model (LLM) outputs in the medical domain. You’ll assess AI-generated clinical content for medical accuracy, safety, and relevance — contributing to the development of responsible AI in healthcare. Main tasks listed: Review AI-generated medical text for accuracy, harmfulness, and completeness, with focus on medical field; Evaluate diagnoses, treatment plans, and summaries for medical cases; Provide expert feedback to improve medical integrity and safety of LLM outputs; Collaborate with AI researchers and clinicians to align model performance with evidence-based medical standards.

We are seeking highly qualified Domain Experts (SMEs) to support the evaluation, testing, and improvement of advanced Large Language Models (LLMs). You will apply your subject-matter expertise to assess AI-generated responses, identify knowledge gaps, design challenging prompts, and improve model accuracy, reliability, and reasoning. Main tasks listed: Create complex, domain-specific prompts to test LLM capabilities; Evaluate AI-generated responses for factual accuracy, reasoning, relevance, and overall quality; Identify factual errors, logical inconsistencies, knowledge gaps, and model weaknesses; Develop challenging test cases and edge cases that expose model limitations.

We are seeking highly motivated Team Management to support the evaluation and improvement of cutting-edge Large Language Models (LLMs). In this role, you will analyze structured data, create challenging prompts, evaluate AI-generated responses for factual accuracy and reasoning quality, and provide evidence-backed feedback to improve model performance. We are looking for curious, detail-oriented professionals who enjoy solving complex problems and evaluating AI systems. Main tasks listed: Create challenging prompts that evaluate an LLM’s ability to retrieve, analyze, and reason over structured data; Assess AI-generated responses for factual accuracy, logical reasoning, and completeness; Identify model failures, inconsistencies, hallucinations, and reasoning gaps; Validate model outputs using provided datasets and supporting evidence.

We are looking for a detail-oriented QA Analyst to evaluate and compare responses generated by multiple chatbots. The role involves reviewing outputs against defined guidelines, identifying inaccuracies or quality issues, and providing a clear final assessment for each evaluation task. Main tasks listed: Evaluate and compare responses generated by multiple chatbots; Assess responses for accuracy, relevance, completeness, clarity, and adherence to guidelines; Identify errors, inconsistencies, missing information, and potential quality issues; Provide structured feedback and final assessments for each task.

We are seeking experienced in Biology help evaluate and enhance large language model (LLM) outputs related to nutrition, dietary habits, and healthy eating. You’ll assess AI-generated content for scientific accuracy, safety, and relevance — contributing to the development of responsible AI in nutrition and wellness. Selected talents will label and evaluate data related to food intake, dietary patterns, and nutrition information to support AI models focused on nutrition tracking, coaching, or research. Main tasks listed: Annotate food items, portion sizes, meal composition, and nutrient content from text, images, or logs; Classify dietary patterns (e.g., macronutrient balance, meal timing, dietary restrictions/preferences); Verify accuracy of nutritional data against trusted references (e.g., food composition databases); Identify and flag mislabeled, inconsistent, or culturally ambiguous food entries.