Job Overview
Location
Germany
Job Type
Contract
Category
Data Science
Date Posted
May 19, 2026
Full Job Description
đź“‹ Description
- • Design advanced, deterministic mathematical problems specifically for training and evaluating frontier AI models in technical reasoning domains
- • Ensure every problem has exactly one verifiable correct answer, with no ambiguity or multiple interpretations
- • Develop complete, meticulously verified solutions that clearly document each step of the mathematical reasoning process
- • Create problems that test deep conceptual understanding and logical deduction, avoiding reliance on memorization or pattern recognition
- • Construct computational workflows using Python and associated libraries (e.g., numpy, scipy, pandas) where appropriate to generate or validate problem outputs
- • Maintain technical precision in all problem formulations, ensuring reproducibility and adherence to mathematical rigor
- • Produce all content in clear, professional English with flawless grammar, syntax, and terminology
- • Collaborate remotely to deliver high-quality STEM training data used directly in AI model training and evaluation pipelines at leading AI laboratories
- • Align problem designs with real-world mathematical workflows to reflect authentic challenges faced in academic and applied research settings
- • Submit problems and solutions in a structured format that enables seamless integration into AI training and benchmarking systems
- • Maintain consistency in problem difficulty to challenge state-of-the-art AI systems without introducing noise or unresolvable ambiguities
- • Review and validate all outputs against established mathematical principles to eliminate errors before submission
- • Work independently within a 20-hour weekly commitment, meeting deadlines for iterative problem sets over a two-month contract period
- • Adapt problem complexity based on feedback from AI evaluation results to continuously improve dataset efficacy
- • Ensure all materials are copyright-compliant and free of plagiarized or proprietary content from external sources
- • Document design rationale for each problem, explaining why it effectively tests reasoning capabilities beyond surface-level computation
- • Maintain a systematic record of problem variants, solution paths, and computational validation steps for audit and future reference
- • Contribute to the development of a scalable, high-fidelity mathematical training dataset that enhances AI reasoning across algebra, analysis, number theory, combinatorics, and other core domains
- • Work in close alignment with AI researchers and data engineers to ensure problem specifications meet technical requirements for model ingestion and evaluation
- • Adhere to strict quality control protocols to ensure every submitted problem-solution pair meets the highest standards of mathematical accuracy and clarity
- • Participate in periodic reviews of dataset performance and refine future problem sets based on AI model failure modes and reasoning gaps
- • Maintain professional communication and responsiveness throughout the contract term to support timely delivery and iterative improvements
🎯 Requirements
- • Master’s or PhD in Mathematics or a closely related field
- • Strong research or industry experience involving mathematical modeling, proof-based reasoning, applied mathematics, or computational mathematics
- • Strong Python skills; comfort with libraries such as numpy, scipy, pandas, or similar
- • Solid grasp of algorithms, numerical methods, and computational approaches
- • Ability to design original, difficult problems that mirror real mathematical workflows
- • Excellent attention to detail and technical writing skills in English
🏖️ Benefits
- • Compensation up to 40 USD per hour
- • Remote work arrangement
- • Contract duration of 2 months with potential for extension
- • Immediate start available
Skills & Technologies
Python
Pandas
NumPy
Remote
Degree Required
About Anyone AI Inc.
Anyone AI provides no-code computer-vision infrastructure that lets companies build, train and deploy image and video models without machine-learning teams. Its cloud platform automates data labeling, model optimization and edge deployment for retail, manufacturing, logistics and healthcare use cases. The company offers pre-trained APIs for object detection, counting and anomaly identification, plus dashboards for continuous monitoring and compliance. Founded in 2021, it targets enterprises seeking rapid AI adoption while avoiding costly specialists and infrastructure setup.
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