Help shape the future of AI by designing challenging math problems that test and improve reasoning in cutting-edge models. We create high-quality STEM training data for frontier AI models. Our data is used directly in training and evaluation pipelines at leading AI labs to improve model reasoning in technical domains.
In this role, you will work on cutting-edge initiatives to fine-tune large language models by leveraging your deep analytical skills and mathematics expertise. The ideal candidate possesses a strong foundation in Mathematics —spanning advanced engineering entrance levels through graduate and PhD-level concepts—and the ability to break down complex phenomena into clear, step-by-step reasoning. Main tasks listed: In this role, you will help set the benchmark for AI capabilities in advanced physical sciences. Your day-to-day responsibilities will include:; Problem Creation & Solutioning: Designing and solving challenging physics problems that test the boundaries of large language models; Authoring Gold-Standard Data: Creating clear, high-quality, step-by-step solutions with detailed and articulated reasoning; Research Collaboration: Working with LLM researchers to align task designs with evaluation goals, targeting key areas where models struggle (e.g., symbolic manipulation, abstraction, multi-step reasoning).
We are seeking Mathematics experts to develop realistic, terminal-based scientific tasks for Terminal Bench Science. You will design tasks involving numerical analysis, optimization, statistics, mathematical modeling, probability, dynamical systems, and computational mathematics. The role focuses on evaluating whether AI agents can formulate mathematical problems, implement reliable algorithms, operate in a terminal environment, debug numerical workflows, and produce verifiable computational results. Main tasks listed: Design and build authentic computational mathematics tasks — translate mathematical and research workflows into self-contained, multi-step terminal environments, complete with datasets, equations, model definitions, constraints, and expected outputs; Implement expert solutions using Python, R, Julia, C/C++, Bash, or other relevant tools, covering areas such as optimization, numerical integration, differential equations, matrix computation, statistical inference, stochastic modeling, or algorithm analysis; Define rigorous grading criteria, including numerical accuracy, convergence, complexity, feasibility, and mathematical correctness, along with appropriate tolerances, stopping criteria, stability requirements, and reproducibility controls; Develop automated tests and debug issues — validate results across edge cases and alternative valid implementations, and troubleshoot problems involving floating-point precision, solver failures, conditioning, convergence, and performance.
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, 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 that models might get wrong, and You would articulate the correct answer & 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.
Design original and challenging mathematics problems that test the reasoning limits of large language models, especially in multi-step, abstract, and proof-based settings. Solve problems independently and write detailed, logically structured solutions with clear justifications. Main tasks listed: Design original and challenging mathematics problems that test the reasoning limits of large language models, especially in multi-step, abstract, and proof-based settings; Solve problems independently and write detailed, logically structured solutions with clear justifications; Review model-generated solutions, identify mathematical errors or missing arguments, and provide precise feedback, annotations, and corrections.; Contribute to defining new evaluation benchmarks based on Mathematics curricula spanning from early undergraduate to PhD-level topics.
We’re looking for mathematics specialists who live and breathe algebra, calculus, number theory, linear algebra, differential equations, statistics, geometry, mathematical logic, and discrete mathematics. You’ll challenge advanced language models on topics like real and complex analysis, optimization theory, mathematical proofs, set theory, probability distributions, cryptographic algorithms, and applied mathematics—documenting every failure mode so we can harden model reasoning. On a typical day, you will converse with the model on classroom problems and theoretical mathematics questions, verify factual accuracy and logical soundness, capture reproducible error traces, and suggest improveme
We’re looking for mathematics specialists who live and breathe algebra, calculus, number theory, linear algebra, differential equations, statistics, geometry, mathematical logic, and discrete mathematics. You’ll challenge advanced language models on topics like real and complex analysis, optimization theory, mathematical proofs, set theory, probability distributions, cryptographic algorithms, and applied mathematics—documenting every failure mode so we can harden model reasoning. On a typical day, you will converse with the model on classroom problems and theoretical mathematics questions, verify factual accuracy and logical soundness, capture reproducible error traces, and suggest improveme
We’re looking for mathematics specialists who live and breathe algebra, calculus, number theory, linear algebra, differential equations, statistics, geometry, mathematical logic, and discrete mathematics. You’ll challenge advanced language models on topics like real and complex analysis, optimization theory, mathematical proofs, set theory, probability distributions, cryptographic algorithms, and applied mathematics—documenting every failure mode so we can harden model reasoning. On a typical day, you will converse with the model on classroom problems and theoretical mathematics questions, verify factual accuracy and logical soundness, capture reproducible error traces, and suggest improveme
We’re looking for mathematics specialists who live and breathe algebra, calculus, number theory, linear algebra, differential equations, statistics, geometry, mathematical logic, and discrete mathematics. You’ll challenge advanced language models on topics like real and complex analysis, optimization theory, mathematical proofs, set theory, probability distributions, cryptographic algorithms, and applied mathematics—documenting every failure mode so we can harden model reasoning. On a typical day, you will converse with the model on classroom problems and theoretical mathematics questions, verify factual accuracy and logical soundness, capture reproducible error traces, and suggest improveme
We’re looking for mathematics specialists who live and breathe algebra, calculus, number theory, linear algebra, differential equations, statistics, geometry, mathematical logic, and discrete mathematics. You’ll challenge advanced language models on topics like real and complex analysis, optimization theory, mathematical proofs, set theory, probability distributions, cryptographic algorithms, and applied mathematics—documenting every failure mode so we can harden model reasoning. On a typical day, you will converse with the model on classroom problems and theoretical mathematics questions, verify factual accuracy and logical soundness, capture reproducible error traces, and suggest improveme