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Lead a pod of about 5–10 trainers building terminal-based materials science tasks for a frontier AI training and evaluation project: review tasks end to end (DFT, molecular dynamics, thermodynamics, crystallography), check scientific correctness and reproducibility, review automated graders and mentor trainers.
Lead a pod of trainers building terminal-based chemistry tasks for Terminal Bench Science: review tasks end to end for chemical correctness, reproducibility, safety and grader reliability (units, convergence, stereochemistry, force fields), and coach trainers.
Lead a pod of trainers building terminal-based physics tasks for Terminal Bench Science: review every task end to end (datasets, simulation inputs, environments, reference solutions, automated tests) for physical correctness, reproducibility and grader reliability, and coach trainers.
Lead a pod of 5–10 trainers building terminal-based mathematical tasks for Terminal Bench Science: review problem statements, environments, reference solutions and automated tests for correctness, stability and reproducibility, design graders and mentor trainers.
Five-week contract for computational life science experts: design realistic multi-step agentic workflows where AI agents analyse scientific data, write and run code and produce verifiable results, with reproducible expert solutions and grading criteria. At least 6 hours a day and 40 hours a week, with 4 hours' overlap with U.S. Pacific time.
We are seeking an experienced Mechanical or Aerospace Engineering expert to lead a team of technical trainers developing realistic, terminal-based engineering tasks for a frontier AI training and evaluation initiative. In this role, you will oversee a pod of approximately 5–10 trainers, review engineering tasks for technical accuracy, reproducibility, and evaluation quality, and ensure that tasks reflect authentic mechanical and aerospace engineering workflows. Main tasks listed: Lead and mentor a pod of technical trainers, ensuring consistent quality, productivity, and timely delivery of engineering tasks; Review engineering tasks end to end, including problem statements, geometry and mesh files, simulation inputs, material properties, reference solutions, and automated tests; Validate tasks involving finite-element analysis (FEA), computational fluid dynamics (CFD), thermodynamics, heat transfer, dynamics, robotics, flight simulation, propulsion, and orbital mechanics; Ensure tasks reflect realistic mechanical and aerospace engineering workflows and require meaningful multi-step technical reasoning.
We are seeking an experienced Mechanical Design & Analysis Expert with top-tier automotive or aerospace engineering pedigree to design datasets that will help our customers train and evaluate advanced AI models against real-world mechanical engineering workflows. Main tasks listed: Convert real-world mechanical engineering challenges into structured test scenarios with defined inputs, requirements, kinematic/geometric constraints, and verified golden reference solutions; Design clear scoring rubrics & programmatic validation rules for automated task verification by software engineers (e.g., verifying stress concentrations, mesh convergence, boundary conditions, tolerance stacks, GD&T adherence); Assess the behavior of state-of-the-art AI agents to diagnose & analyse failure modes; Design and manage automated and human-expert-in-the-loop QA/QC workflows to ensure dataset quality.
We are hiring US-based academic chemists to support the curation and evaluation of high-quality chemistry data for frontier AI models and research laboratories. This is the Senior Reviewer track of the project. You will review complex chemistry problems and AI-generated solutions, resolve disagreements among reviewers, develop evaluation frameworks, and serve as a subject-matter advisor to client teams assessing AI model outputs.
Responsible for developing electronic hardware designs from initial requirements through component selection, schematic design, PCB layout, and design validation, with a focus on power electronics and automotive applications. Main tasks listed: Analyze product requirements and translate them into hardware specifications; Develop circuit architectures and select appropriate electronic components based on electrical ratings, performance, reliability, availability, and cost; Design schematics for DC-DC converters, power supplies, battery management, protection circuits, and automotive power electronics; Perform component-level calculations and assess voltage, current, power dissipation, thermal performance, and protection requirements.
Responsible for end-to-end electronic hardware development, from requirements analysis and circuit design to component selection, schematic capture, PCB layout, and design verification for analog, mixed-signal, sensor, communication, and RF applications. Main tasks listed: Interpret functional and electrical requirements and convert them into circuit-level specifications; Develop circuit architectures and select suitable components using datasheets, application notes, and design calculations; Design analog, mixed-signal, sensor-interface, signal-conditioning, industrial-interface, and RF circuits; Develop schematics and associated BOMs, including suitable component alternatives where required.
Responsible for developing digital and high-speed electronic hardware from requirements definition and component selection through schematic design, PCB layout, and design verification. Main tasks listed: Analyze system requirements and develop hardware specifications and circuit architectures; Select processors, microcontrollers, FPGAs, memories, interface ICs, power-management components, and supporting circuitry; Design schematics for embedded systems, digital interfaces, communication boards, and high-speed electronic products; Develop multilayer PCB layouts with appropriate stack-up planning, reference planes, controlled impedance, differential-pair routing, and timing constraints.
We are seeking an experienced Electrical Engineering or Computer Science expert to lead a team of technical trainers developing realistic, terminal-based scientific and engineering tasks for a frontier AI training and evaluation initiative. In this role, you will oversee a pod of approximately 5–10 trainers, review technical tasks for accuracy, reproducibility, and evaluation quality, and ensure tasks reflect authentic computer science, software systems, and electrical engineering workflows. Main tasks listed: Lead and mentor a pod of technical trainers, ensuring consistent quality, productivity, and timely delivery of scientific and engineering tasks; Review technical tasks end to end, including problem statements, codebases, circuit netlists, hardware description languages (HDL), datasets, computational environments, reference solutions, and automated tests; Validate tasks involving high-performance computing (HPC), parallel computing, algorithms, distributed systems, compilers, operating systems, databases, ML systems, GPU computing, circuit design, signal processing, power systems, and embedded systems; Ensure tasks reflect realistic software engineering, research, and electrical engineering workflows requiring meaningful multi-step technical reasoning.
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.
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 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 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.
We are seeking experienced Electrical Engineers to design, solve, and review simulation-led engineering tasks used to train and evaluate advanced AI models. The role requires strong technical fundamentals, practical simulation expertise, and the ability to produce clear, reproducible engineering solutions. We are hiring for a PAA-based project, seeking candidates with strong hands-on experience in CAD modeling and simulation tools. Main tasks listed: Develop CAD models and perform simulation/analysis for aero, mech and elec components; Validate designs using industry-standard tools (e.g., CATIA, SolidWorks, ANSYS, MATLAB); Develop realistic electrical engineering problem statements, simulation models, calculations, schematics, and supporting technical assets; Define inputs, assumptions, constraints, operating conditions, output metrics, and objective acceptance criteria.
We are seeking an experienced Civil or Structural Engineering expert to lead a pod of trainers building realistic, terminal-based technical tasks for Terminal Bench Science. You will review every task your trainers produce for engineering correctness, reproducibility, and grader reliability, and coach trainers to consistently deliver high-quality tasks. Main tasks listed: Review engineering tasks end to end, including problem statements, structural and geotechnical models, load cases, simulation data, computational environments, reference solutions, and automated tests; Validate tasks involving structural analysis, finite-element methods (FEA), earthquake and wind engineering, structural dynamics, geotechnical modeling, hydraulics, hydrology, transportation, and infrastructure systems; Ensure tasks require genuine multi-step engineering reasoning and reflect realistic civil and structural engineering workflows; Verify engineering accuracy across units, equilibrium, boundary conditions, load combinations, design codes, numerical stability, convergence, and safety factors.
We are seeking an experienced Chemical Engineering expert to lead a team of technical trainers developing realistic, terminal-based engineering tasks for a frontier AI training and evaluation initiative. In this role, you will oversee a pod of approximately 5–10 trainers, review chemical engineering tasks for technical accuracy, reproducibility, and evaluation quality, and ensure tasks reflect authentic chemical engineering workflows. Main tasks listed: Lead and mentor a pod of technical trainers, ensuring consistent quality, productivity, and timely delivery of chemical engineering tasks; Review engineering tasks end to end, including problem statements, reaction kinetics, thermodynamic and property data, process flowsheets, computational environments, reference solutions, and automated tests; Validate tasks involving reaction engineering, thermodynamics, phase equilibria, transport phenomena, separation processes, process simulation, process control, optimization, combustion, and electrochemical engineering; Ensure tasks reflect realistic chemical engineering workflows and require meaningful multi-step technical reasoning.
We are seeking experienced Earth Sciences experts to develop realistic, terminal-based scientific and computational tasks for a frontier AI training and evaluation initiative. In this role, you will design challenging scientific tasks involving climate science, atmospheric processes, geophysics, oceanography, geology, hydrology, remote sensing, and environmental modeling. Main tasks listed: Design realistic, multi-step scientific tasks based on authentic Earth Sciences, climate, geospatial, environmental, and geophysical research workflows; Prepare and process scientific datasets involving climate, weather, atmospheric conditions, oceanography, geology, hydrology, satellite imagery, and environmental systems; Develop computational tasks involving geospatial analysis, time-series processing, numerical modeling, interpolation, forecasting, remote sensing, and environmental risk analysis; Build reproducible, terminal-based computational environments using scientific libraries, command-line tools, and appropriate dependencies. The listing says the work can involve sensitive or graphic content.