Language: English

We are seeking coding experts with strong language skills to support AI training and evaluation projects. You will apply your programming expertise to review code, solve technical problems, and improve the accuracy and clarity of AI-generated responses in your language of expertise. Main tasks listed: Write, review, debug, and optimize code for various programming tasks; Evaluate AI-generated code for correctness, efficiency, readability, and adherence to instructions; Create and review coding prompts, solutions, and technical explanations in your language of expertise; Ensure technical responses are clear, linguistically accurate, and use appropriate programming terminology.

Turing invites Healthcare Experts to join projects that fine-tune AI models. If you enjoy applying clinical knowledge, analyzing complex medical scenarios, and providing clear, structured feedback, this is your chance to put your expertise to work in a new way. Your healthcare experience will help shape how the next generation of AI understands and reasons about medical topics and patient care. Main tasks listed: Review and evaluate AI-generated responses to medical and healthcare scenarios; Apply a structured rubric to assess clinical accuracy, reasoning, completeness, and patient-safety considerations; Identify gaps, edge cases, unsafe recommendations, and blind spots in medical reasoning; Provide detailed annotations and written feedback to refine AI models.

We are seeking an analytical researcher and red-teaming specialist to build evidence-based web-research benchmark tasks that reliably expose weaknesses in state-of-the-art (SOTA) AI models (e.g., Claude Opus 5 Max). In this role, you will discover hard-to-surface facts, build precise research tasks around them, test them directly against leading LLMs, and diagnose the exact failure mechanisms in the model’s search and reasoning paths. Main tasks listed: Obscure Fact Discovery: Deeply research niche topics to identify factual ground truths that cannot be surfaced via simple, direct search queries; Source Verification: Rigorously verify facts against primary or highly credible sources, cross-check for contradictory evidence, and document exact source URLs; Task Construction: Draft clear, answerable benchmark tasks designed specifically to expose structural weaknesses in model research strategies; Red-Teaming & Model Testing: Execute tasks against designated SOTA models to confirm they reliably trigger intended model failures.

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 seeking Life Sciences Subject Matter Experts to develop advanced scientific reasoning tasks for LifeSciBench. Unlike coding-focused benchmarks, this role emphasizes deep biological knowledge, scientific interpretation, and rigorous reasoning. You will create challenging questions based on realistic scientific scenarios, experimental results, biological data, figures, literature-style evidence, and research problems. This is a non-code benchmark: tasks are not executed, and no programming is required. Main tasks listed: Design novel, challenging life sciences problems requiring advanced scientific reasoning; Create tasks grounded in realistic research scenarios, experiments, biological datasets, figures, sequences, structures, or scientific evidence; Develop clear questions with well-defined and objectively defensible answers; Write rigorous expert reference answers explaining the scientific reasoning required.

We are seeking Computational Life Sciences experts with strong scientific programming skills to develop complex, realistic tasks for Agentic Life Sciences. You will design tasks where AI agents must independently navigate scientific data, write and execute code, use computational tools, troubleshoot intermediate results, and produce scientifically valid final outputs. The goal is to evaluate whether AI systems can perform authentic multi-step scientific work — not simply answer scientific questions.

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 looking for a detail-oriented Business Analyst to support a project involving the evaluation of multiple chatbot responses. The role will require analyzing business requirements, comparing chatbot outputs, conducting structured evaluations, and providing final assessments based on defined criteria. Main tasks listed: Gather, analyze, and document business requirements; Collaborate with stakeholders to understand business needs and objectives; Translate business requirements into clear functional specifications; Analyze workflows, processes, and data to identify gaps and improvement areas.

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.

Turing invites Finance and Accounting Experts to join projects that fine-tune AI models. If you enjoy analyzing financial information, applying professional judgment, and providing clear, structured feedback, this is your chance to put your expertise to work in a new way. Your experience in accounting, investment banking, or wealth management will help shape how the next generation of AI understands and reasons about financial topics. Main tasks listed: Review and evaluate AI-generated responses to financial, accounting, valuation, and investment-related scenarios; Apply a structured rubric to assess accuracy, calculations, assumptions, reasoning, and risk awareness; Identify gaps, edge cases, and blind spots in financial analysis; Provide detailed annotations and written feedback to refine AI models.