Long-running remote contract on a PII anonymization program: work through business documents and structured records (CRM exports, email, tickets, chat logs, accounting data), confirm, reject, add and correctly type personal information, find PII that automated detection missed and group related people and organizations consistently. Reviewers check the work, and the listing says strong writers are the pool reviewers are promoted from.
Remote contract work for recent graduates and generalists: write original, challenging multi-step question-and-answer pairs across diverse subjects, research and triangulate sources, test questions against AI models and adjust their difficulty, and document each answer with clear citations. No prior AI experience is required.
Ongoing weekly study for existing users of the Meta Muse or Instinct assistant app: keep using the assistant in at least three areas of your life, log and rate the proactive messages it sends you, and export your weekly conversations with personal details removed. This study involves sharing your own app conversations: read the privacy and consent terms on the official page before applying.
We are seeking creative and detail-oriented Image Annotation QA who can create high-quality stylized assets from briefs and references. The ideal candidate should have strong skills in 3D modeling, texturing, lighting, shading, rendering, and material creation. Estimated earning potential of approximately $7hour Up to 40 hours/week; Full-time artists working up to 20 hours/week are welcome Main tasks listed: Create stylized 3D models and digital assets; Work with low-poly, voxel, handcrafted, and material-driven styles; Recreate textures such as clay, fabric, paper, and textiles; Apply strong skills in topology, UV mapping, lighting, shading, and rendering.
We are seeking US-based generalist raters to participate in Gemini Personalization Evals. In this role, raters will perform generalist evaluation work using personalized prompts designed to retrieve context and data across connected Google apps. This work may involve recording or sharing personal data (for example voice, video or account activity): read the consent and privacy terms on the official page before applying.
In this role, you will be working on projects to help fine-tune large language models (like ChatGPT) using your strong analytical and English comprehension skills. The ideal candidate should have the ability to read, summarize, review and break down large content into smaller logical blocks, conduct research online, validate claims made in content through online research, and work with the LLM (Large Language Models) to solve puzzles! The projects will also help you learn how to leverage AI to be a better analyst. Main tasks listed: You would spend time answering a variety of interesting analytical questions and creating scenarios that can train the LLM models to get better. Here are a couple of examples which models might get wrong and you would have to give the correct answer and explanation to enable the models to learn:; Based on a given distribution of sales by month across locations, could you analyze which location has grown the most? (Hint: what time period should we look at? should we account for sudden variability at the beginning?); In a small town, there are four distinct neighborhoods: Oak, Pine, Maple, and Elm. A postman is assigned to deliver mail and can only deliver to two neighborhoods in one day, with certain rules (e.g. Oak is always visited before Pine). If he delivers to Oak and Elm on the first day, which neighborhoods does the carrier deliver to on the second day?; Note: No other prior specialized domain experience is needed.
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.
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…
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 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.