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About Terac: Overview: We are conducting a paid study to evaluate common accounting workflows and software usage. We need experienced accounting professionals to walk us through how they manage daily financial tasks using standard industry tools.Availability: 99+ spots leftCompensation: $750 / taskReferral Reward: Earn up to $1,000 per person you refer.

About Turing: 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 proof of concept into proprietary intelligence with systems that perform reliably, deliver measurable impact, and drive lasting results on the P&L.About the RoleWe are seeking Life Sciences Subject Matter Experts to design advanced scientific-reasoning tasks for LifeSciBench. This is a non-coding role focused on biological knowledge, experimental interpretation, data analysis, and rigorous scientific reasoning.You will create challenging, objectively defensible problems based on realistic research scenarios, experimental results, biological data, figures, sequences, structures, and literature-style evidence. Tasks should test synthesis and interpretation rather than factual recall and help distinguish advanced AI reasoning capabilities.Responsibilities Design novel, graduate-level life sciences problems grounded in realistic research contexts. Develop clear questions and rigorous reference answers with defensible scientific reasoning. Interpret experiments, datasets, figures, sequences, structures, and other biological evidence. Validate biological claims, calculations, assumptions, and conclusions. Identify ambiguity, alternative interpretations, and insufficiently constrained questions. Ensure tasks are self-contained, reproducible where applicable, and clearly documented. Incorporate reviewer feedback while maintaining quality and throughput.Required Qualifications Ph.D., postdoctoral experience, or equivalent advanced research experience in the life sciences. Strong expertise in at least one biological discipline. Demonstrated ability to interpret scientific experiments, data, and research findings. Strong scientific writing skills and attention to precision.Relevant backgrounds include molecular biology, genetics and genomics, cell biology, biochemistry, neuroscience, microbiology, immunology, evolutionary biology, ecology, structural biology, biophysics, developmental biology, cancer biology, pharmacology, and related life sciences disciplines.Preferred Qualifications Experience designing graduate-level problems, assessments, or research exercises. Experience reviewing scientific manuscripts or research. Ability to translate complex scientific concepts into precise, self-contained questions. Experience evaluating AI-generated scientific responses or working with AI/ML evaluation datasets. Peer-reviewed publications or graduate-level teaching and mentoring experience.Important NoteThis role does not involve programming or executing code. For coding-based or workflow-oriented opportunities, please explore GeneBench Pro, Agentic Life Sciences, or Terminal Bench Science.Offer Details: Commitments Required: at least 8 hours per day and minimum 40 hours per week with 4 hours of overlap with PST.  Engagement type: Contractor assignment/freelancer (no medical/paid leave) Duration of contract: 1 monthBenefits Opportunity to work on cutting-edge AI projects. Competitive compensation. Flexible working hours and remote work environment.Evaluation Process Job interest form Assessment  Based on the answers and scores, you will be contacted to discuss the pre-onboarding requirements

About Turing: Role Overview:Turing is building one of the most rigorous STEM AI training datasets in the industry. The SciCode project involves creating high-quality scientific coding tasks that are used to train and evaluate frontier AI models. As a SciCode Trainer, you will be directly contributing to cutting-edge AI research by authoring, implementing, and reviewing complex scientific problems across core STEM disciplines.  Responsibilities: Write scientific problem specifications consisting of one main problem and a minimum of 3 sub-problems, all logically connected and progressively building toward the main problem solution Implement verified golden solutions in Python with complete unit test coverage Design discriminative test cases that clearly differentiate correct from incorrect model outputs Run QC validation checks on the Turing Central Task Platform (CTP) including Tier 1 structure checks and Tier 2 quality rubrics Iterate on tasks based on QC feedback to meet Pass@K evaluation criteria across multiple LLM judges (GPT, Gemini, Nemotron)  Maintain high output quality with a low rework rate, targeting consistent L1 approval on first submission  Participate in sync calls for reviews, feedback sessions, and project standups during overlap hoursRequired Qualifications:  Master's or PhD in  Physics. Strong Python programming skills with experience in scientific computing Ability to write rigorous, well-posed scientific problems with clear constraints and expected outputs  Attention to detail - tasks must meet strict rubrics for well-posedness, test case discriminativeness, scientific correctness, and determinism  Prior experience in AI data annotation, research, or scientific writing Familiarity with LLM evaluation frameworks or coding benchmarks Experience with libraries such as NumPy, SciPy, SymPy, or domain-specific scientific tools . Published research or academic project experience in a STEM domain Quality StandardsOffer Details: Commitments Required : Overlap of 4 hours with PST and  40 hrs/week  Engagement type : Contractor assignment/freelancer (no medical/paid leave) Duration of contract :  8 weeks  Location : Bangladesh, Brazil, Colombia, Egypt, Ghana, India, Pakistan, Indonesia, Kenya, Nigeria, Turkey, Vietnam

About Turing: Role Overview:We are staffing a frontier AI initiative that requires strong Engineering experts to develop realistic, terminal-based scientific and technical tasks used to train and evaluate AI agents.The work involves translating authentic engineering workflows into reproducible computational tasks that test modeling, simulation, optimization, data processing, debugging, and technical validation. The role spans disciplines including mechanical, electrical, chemical, aerospace, civil, materials, biomedical, robotics, and control systems engineering.What you'll do:Design realistic, multi-step terminal tasks based on real-world engineering and scientific workflows.Create engineering datasets, simulation inputs, geometry files, sensor data, design constraints, and configuration files.Develop expert solutions using Python, C/C++, Julia, MATLAB/Octave, Bash, or relevant engineering software.Build reproducible, containerized environments with appropriate engineering tools and pinned dependencies.Develop tasks involving simulation, numerical analysis, optimization, control systems, signal processing, finite-element concepts, CAD-related data, and engineering design.Create automated tests and objective grading criteria that validate engineering correctness, including units, physical constraints, tolerances, convergence, stability, boundary conditions, and numerical behavior.Debug solver, dependency, workflow, precision, and performance issues and clearly document assumptions, requirements, expected outputs, and edge cases.What we're looking for:Ph.D., postdoctoral experience, or equivalent advanced technical experience in an Engineering discipline such as mechanical, electrical, chemical, aerospace, civil, materials, biomedical, robotics, or control systems.Strong scientific programming skills in Python, C/C++, Julia, MATLAB/Octave, Bash, or another relevant language.Hands-on experience working in Linux or terminal-based environments.Experience with engineering simulation, modeling, numerical analysis, optimization, signal processing, control systems, or technical data analysis.Strong understanding of numerical methods, engineering units, physical constraints, boundary conditions, and technical validation.Ability to build, debug, and validate reproducible computational engineering workflows.Nice to have:Experience with scientific libraries such as NumPy, SciPy, pandas, matplotlib, SymPy, or PyTorch.Familiarity with engineering tools such as OpenFOAM, CalculiX, FEniCS, ROS, LTspice-compatible workflows, QEMU, or similar software.Experience with finite-element methods (FEM), computational fluid dynamics (CFD), robotics, embedded systems, control systems, or digital twins.Familiarity with Docker, Git, CI/CD, automated testing, or HPC environments.Experience developing technical benchmarks, programming tasks, simulation-based evaluations, or automated graders.Experience evaluating AI coding or terminal agents or working in research software engineering.Publications, patents, open-source contributions, or industry experience involving computational engineering.Offer Details:Commitments Required: At least 6 hours per day and minimum 40 hours per week with overlap of 4 hours with PST. Employment type  : Contractor assignment (no medical/paid leave)Duration of contract : 5 week [expected start date is next week]Payment type: Pay Per Task $300/per approved task