Generative AI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. Although every project is unique, you might typically: - Content Creation & Refinement: Create and refine content to ensure accuracy and relevance across a variety of topics in Physics, while also developing references and examples of tasks. - Experts Acquisition: Assess the qualification tests of experts, ensuring their competency. - Chat Moderation: Provide support by addressing project-related questions from other experts in Discord chats, especially those related to project guidelines. - Auditing Work: Review and evaluate tasks completed by other experts, ensuring they align with project guidelines. Provide constructive feedback, verify expertise-related information, and edit content as necessary to improve quality.

An insurance company in Nuremberg is looking for a Senior Factor 10 Developer with expertise in IPS and IPM. The project includes developing and optimizing software solutions in the insurance sector, focusing on high performance and reliability. The role requires solid knowledge of Factor 10 and its applications in the insurance industry. Key responsibilities: - Developing and optimizing applications with Factor 10, especially in IPS and IPM. - Collaborating with interdisciplinary teams to ensure seamless integration and functionality. - Analyzing and resolving complex technical issues. - Providing technical guidance and mentoring to junior developers. - Ensuring compliance with industry standards and best practices.

For an AI lab we are looking for Mechanical Engineer with python experience to train an AI model (Large Language Model - LLM). GenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: - Content Creation & Refinement: Create and refine content to ensure accuracy and relevance across a variety of topics in Mechanical Engineering, while also developing references and examples of tasks. - Experts Acquisition: Assess the qualification tests of experts, ensuring their competency. - Chat Moderation: Provide support by addressing project-related questions from other experts in Discord chats, especially those related to project guidelines. - Auditing Work: Review and evaluate tasks completed by other experts, ensuring they align with project guidelines. Provide constructive feedback, verify expertise-related information, and edit content as necessary to improve quality.

We’re on the hunt for hands-on Python engineers for a new project focused on developing Model Context Protocol (MCP) servers and internal tools for running and evaluating agent behavior. You’ll implement base methods for agent action verification, integrate with internal and client infrastructures, and help fill tooling gaps across the team. What you’ll be doing: - Developing and maintaining MCP-compatible evaluation servers - Implementing logic to check agent actions against scenario definitions - Creating or extending tools that writers and QAs use to test agents - Working closely with infrastructure engineers to ensure compatibility - Occasionally helping with test writing or debug sessions when needed Although we’re only looking for experts for this current project, contributors with consistent high-quality submissions may receive an invitation for ongoing collaboration across future projects.

An AI lab is looking for a freelance chemistry experts to evaluate AI models. The goal of the project is to assess the performance, accuracy, and reliability of AI models applied in chemistry contexts. The role involves working closely with the development team to ensure the models meet industry standards and provide actionable insights. This is a remote part-time role that can be flexibly tailored to your availability – from just a few hours per week to full-time. Key responsibilities: - Evaluate AI models for chemistry applications. - Analyze model outputs and provide feedback for improvement. - Collaborate with the development team to ensure alignment with industry standards. - Document findings and recommendations for model optimization. - Conduct tests to validate model performance and reliability.

An AI lab is looking for a freelance biology experts to evaluate AI models. The goal of the project is to assess the performance, accuracy, and reliability of AI models applied in biology (all areas) contexts. The role involves working closely with the development team to ensure the models meet industry standards and provide actionable insights. This is a remote part-time role that can be flexibly tailored to your availability – from just a few hours per week to full-time. Key responsibilities: - Evaluate AI models for biology applications. - Analyze model outputs and provide feedback for improvement. - Collaborate with the development team to ensure alignment with industry standards. - Document findings and recommendations for model optimization. - Conduct tests to validate model performance and reliability.

Generative AI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. Although every project is unique, you might typically: - Content Creation & Refinement: Create and refine content to ensure accuracy and relevance across a variety of topics in Physics, while also developing references and examples of tasks. - Experts Acquisition: Assess the qualification tests of experts, ensuring their competency. - Chat Moderation: Provide support by addressing project-related questions from other experts in Discord chats, especially those related to project guidelines. - Auditing Work: Review and evaluate tasks completed by other experts, ensuring they align with project guidelines. Provide constructive feedback, verify expertise-related information, and edit content as necessary to improve quality.

For an AI lab we are looking for Machine learning experts to train an AI model (Large Language Model - LLM). GenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: - Design original computational STEM problems that simulate real scientific workflows - Create problems that require Python programming to solve - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks) - Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches - Verify solutions using Python with standard libraries (numpy, pandas, scipy, sklearn) - Document problem statements clearly and provide verified correct answers

- Product and web development in the data-driven field - Shaping the software architecture for new data products - Collaborating in interdisciplinary teams (including data scientists and business developers)

For an AI lab we are looking for Statistics Expert with python experience to train an AI model (Large Language Model - LLM). GenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: - Generate prompts that challenge AI. - Define comprehensive scoring criteria to evaluate the accuracy of the AI’s answers. - Correct the model’s responses based on your domain-specific knowledge.

- You develop modern, high-performance web frontends with React, TypeScript, HTML and CSS - You implement responsive designs with a focus on accessibility and performance - You plan and execute unit and integration tests (for example with Playwright) - You troubleshoot issues in development, test or live environments

For an AI lab we are looking for Ruby Developer to train an AI model (Large Language Model - LLM). You help AI to make sense of the world. As consultant, you may be invited to take part in online projects to train the model in your domain of expertise. This flexible role accommodates both experts seeking part-time engagement (minimum few hours/week) and those interested in full-time opportunities. - Code generation and code review - Prompt evaluation and complex data annotation - Training and evaluation of large language models - Benchmarking and agent-based code execution in sandboxed environments - Working across multiple programming languages (Python, JavaScript/TypeScript, Rust, SQL, etc.) - Adapting guidelines for new domains and use cases - Collaborating with project leads, solution engineers, and supply managers on complex or experimental projects

For replacing the consent layers that have so far been delivered by third-party CMPs on the web for our international brands, these layers will be newly implemented so they can be maintained and deployed in-house. This requires solid knowledge of TypeScript, Vue.js and classic web technologies (HTML and CSS). The goal is to deliver executable code that meets all requirements and includes automated tests proving correct functionality. What exactly is the scope of work: The main focus is on developing elements to decide on the approach and implementing measures along the resulting project path. This specifically includes the following service packages: - Implementation of code - Implementation of executable tests that must pass before delivery, test coverage >= 80% - Creation of documentation for the code - Creation of brand-specific cmp-config files. - Creation of a project (including asset management requirements) as a copy of the Consent Management Platform. - Removal of netID references. - Creation of brand-specific settings and files for custom purposes/vendors. - Addition of new brand-specific CSS themes (variable values, logos etc.). - Inclusion of the required official IAB GVL translations (ES, FR) in the weekly synchronization with GVL - Implementation of I18n and preparation of brand-specific data sources - Implementation of PMC2.0 backend usage modules - Implementation of the playout logic - Implementation of the layer initialization process (mode=default and mode=resurface) - CDN upload and release process - Project documentation Project implementation: - The desired result should be written in TypeScript and Vue.js, built with Vite, tests with Vitest.

For an AI lab we are looking for mathematicians with Python experience to train an AI model (Large Language Model - LLM). As a consultant, you may be invited to take part in online projects to train the model in your field of expertise. This flexible role suits both experts seeking part-time engagement (minimum a few hours/week) and those interested in full-time opportunities. Although every project is unique, you might typically: - Design original computational mathematics problems that simulate real mathematical research workflows. - Create problems requiring Python programming to solve (using numpy, scipy, sympy). - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks). - Develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis. - Base problems on real research challenges or practical applications from mathematical practice. - Verify solutions using Python with standard mathematical libraries. - Document problem statements clearly and provide verified correct answers. Support in: - Number Theory: Prime factorization, Diophantine equations, modular arithmetic, cryptographic computations. - Combinatorics: Enumerations, partitions, generating functions, combinatorial optimization. - Graph Theory: Network analysis, path finding, graph coloring, spanning trees. - Numerical Analysis: Root finding, numerical integration, differential equations, matrix computations. - Discrete Mathematics: Recurrence relations, algorithmic complexity, discrete optimization. - Algebra: Polynomial computations, group theory calculations, matrix decompositions.

A company is looking for a freelance Civil engineering experts to evaluate AI models. The goal of the project is to assess the performance, accuracy, and reliability of AI models applied in civil engineering contexts. The role involves working closely with the development team to ensure the models meet industry standards and provide actionable insights. Key responsibilities: - Evaluate AI models for civil engineering applications. - Analyze model outputs and provide feedback for improvement. - Collaborate with the development team to ensure alignment with industry standards. - Document findings and recommendations for model optimization. - Conduct tests to validate model performance and reliability.

We’re looking for someone who can design realistic and structured evaluation scenarios for LLM-based agents. You’ll create test cases that simulate human-performed tasks and define gold-standard behavior to compare agent actions against. You’ll work to ensure each scenario is clearly defined, well-scored, and easy to execute and reuse. You’ll need a sharp analytical mindset, attention to detail, and an interest in how AI agents make decisions. Although every project is unique, you might typically: - Designing structured test scenarios based on real-world tasks. - Defining the golden path and acceptable agent behavior. - Annotating task steps, expected outputs, and edge cases. - Working with devs to test your scenarios and improve clarity. - Reviewing agent outputs and adapting tests accordingly

Generative AI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. Although every project is unique, you might typically: - Content Creation & Refinement: Create and refine content to ensure accuracy and relevance across a variety of topics in Physics, while also developing references and examples of tasks. - Experts Acquisition: Assess the qualification tests of experts, ensuring their competency. - Chat Moderation: Provide support by addressing project-related questions from other experts in Discord chats, especially those related to project guidelines. - Auditing Work: Review and evaluate tasks completed by other experts, ensuring they align with project guidelines. Provide constructive feedback, verify expertise-related information, and edit content as necessary to improve quality.

GenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as an AI Tutor in Chemistry, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: - Generate prompts that challenge AI. - Define comprehensive scoring criteria to evaluate the accuracy of the AI’s answers. - Correct the model’s responses based on your domain-specific knowledge.

For an AI lab we are looking for phycists with python experience to train an AI model (Large Language Model - LLM). GenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a phycist, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: - Design original computational physic problems that simulate real research workflows. - Create problems requiring Python programming to solve (using numpy, scipy, sympy). - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks). - Develop problems requiring non-trivial reasoning chains. - Base problems on real research challenges or practical applications from physical practice. - Verify solutions using Python with standard libraries. - Document problem statements clearly and provide verified correct answers.

A company is looking for an experienced Data Engineer to carry out a migration from Snowflake to ClickHouse. The focus is on using Apache Spark for data processing and on managing and optimizing Kubernetes environments. The goal is to build and operate a powerful and scalable data platform. - Executing the migration from Snowflake to ClickHouse - Developing and optimizing data pipelines with Apache Spark - Managing and optimizing Kubernetes clusters - Ensuring the performance and scalability of the data platform - Implementing solutions in Python - Optional: Working with Snowplow for data analytics

For an AI lab, we are looking for a Java Developer to train an AI model (Large Language Model - LLM). You help AI make sense of the world. As a consultant, you may be invited to take part in online projects to train the model in your domain of expertise. This flexible role accommodates both experts seeking part-time engagement (minimum a few hours/week) and those interested in full-time opportunities. - Code generation and code review - Prompt evaluation and complex data annotation - Training and evaluation of large language models - Benchmarking and agent-based code execution in sandboxed environments - Working across multiple programming languages - Adapting guidelines for new domains and use cases - Following project-specific rubrics and requirements - Collaborating with project leads, solution engineers, and supply managers on complex or experimental projects

We are seeking an analytical and technically-minded professional to: - Evaluate AI outputs and processes - Ensure quality, accuracy, and reliability - Identify logical errors, risks, and structural inconsistencies - Provide actionable insights and recommendations to the team Ideal candidates: - Consultants, auditors, analysts, data researchers, or business/technical analysts with strong reasoning skills - Professionals curious about AI, process improvement, and quality evaluation - Problem-solvers who enjoy analyzing complex systems, logic, and scenarios Key Responsibilities: - Lead evaluation of AI outputs and related processes - Review tasks against expected/ideal scenarios; identify gaps and risks - Provide structured, actionable recommendations to engineers, domain experts, and managers - Maintain and improve evaluation guidelines, checklists, SOPs - Suggest new approaches, tools, and processes to enhance AI evaluation

An AI Lab is looking for a AI Trainer for Vibe Coding. This role involves producing accurate, well-reasoned outputs across diverse domains, leveraging automation and AI tools. The position requires expertise in coding and optimizing Python scripts, handling large datasets, improving AI-generated content, and formatting and troubleshooting technical workflows. This is a remote part-time role that can be flexibly tailored to your availability – from just a few hours per week to full-time. Key responsibilities: - Conduct advanced web research and data mining using multiple tools to locate and extract information from official sources. Use LLMs and advanced prompts to refine search strategies and validate data accuracy by cross-referencing authoritative sources. - Perform web scraping and data extraction by navigating complex website structures and multi-level pages (regions → companies → detailed pages). Handle dynamic content, archived pages, and various HTML formats, and organize extracted data into clean, well-formatted CSV files. - Write and optimize Python scripts for data processing and analysis using libraries such as pandas, BeautifulSoup, Selenium, and matplotlib. Transform raw data into structured formats (CSV, JSON, tables) and create visualizations when required. - Carry out data processing and quality assurance by cleaning, validating, and structuring datasets. - - Ensure data integrity across multiple sources, apply formatting specifications, and run verification steps to maintain high output quality. - Apply strong problem-solving and task execution skills to break down complex workflows, troubleshoot technical issues independently, and adapt quickly between different domains and task types with minimal supervision. - Produce clear documentation and high-quality outputs that follow exact requirements for file formats, naming conventions, and data structure. Maintain reproducible workflows and well-organized code.

GenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as an AI Tutor in Biology, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: - Generate prompts that challenge AI. - Define comprehensive scoring criteria to evaluate the accuracy of the AI’s answers. - Correct the model’s responses based on your domain-specific knowledge.

We are seeking experienced data scientists to create computationally intensive data science problems for an advanced AI evaluation project. This is a remote, project-based opportunity for experts who can design challenging problems that require computational methods to solve and mirror the full data science lifecycle - from data acquisition and processing to statistical analysis and actionable business insights. What You'll Do - Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare) - Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn) - Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks) - Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction - Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility - Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency - Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations) - Incorporate big data processing scenarios requiring scalable computational approaches - Verify solutions using Python with standard data science libraries and statistical methods - Document problem statements clearly with realistic business contexts and provide verified correct answers

For an AI lab we are looking for cybersecurity consultants to train an AI model (Large Language Model - LLM). You help AI to make sense of the world. As consultant, you may be invited to take part in online projects to train the model in your domain of expertise. This flexible role accommodates both experts seeking part-time engagement (minimum few hours/week) and those interested in full-time opportunities - Evaluate and red team AI models and agents and machine learning systems for vulnerabilities and safety risks. - Create offline reproducible & auto-evaluable test cases to test safety & capability of AI agents. - Develop and implement automation scripts, custom tools, environments and test harnesses. - Lead or contribute to security research initiatives, especially in AI safety, creating and implementing realistic and challenging attack scenarios for the model. - Advise on cybersecurity best practices and policy implications.

We are the agentic data management platform for production and logistics, where AI Agents powered by a domain specific semantic layer clean, prepare and format data, so that ad-hoc business requests that usually take weeks are answered in seconds, enabling fast data-driven decision making. To further shape and scale this product, we are looking for a (senior) freelance Data & Semantic Layer Architect with a strong focus on conceptual and architectural work (not hands-on implementation in this first phase), who will: - design the overall product and solution architecture (semantic layer, data platform, knowledge base, multi-agent workflows, APIs) - define a feature list and solution roadmap for the first product versions - specify an MVP / prototype for the validation phase (scope, tech stack, integrations, risks) - create a high-level effort estimate and team setup (roles, skills, build-vs-buy) - design the core semantic layer (domains, KPIs, metrics logic, data catalog, business rules).

We’re on the hunt for QAs for autonomous AI agents for a new project focused on validating and improving complex task structures, policy logic, and agent evaluation frameworks. Throughout the project, you’ll have to balance quality assurance, research, and logical problem-solving. This project opportunity is ideal for people who enjoy looking at systems holistically and thinking through scenarios, implications, and edge cases. You do not need a coding background, but you must be curious, intellectually rigorous, and capable of evaluating the soundness and consistency of complex setups. If you’ve ever excelled in things like consulting, CHGK, Olympiads, case solving, or systems thinking — you might be a great fit. What you’ll be doing: - Reviewing evaluation tasks and scenarios for logic, completeness, and realism. - Identifying inconsistencies, missing assumptions, or unclear decision points. - Helping define clear expected behaviors (gold standards) for AI agents. - Annotating cause-effect relationships, reasoning paths, and plausible alternatives. - Thinking through complex systems and policies as a human would to ensure agents are tested properly. - Working closely with QA, writers, or developers to suggest refinements or edge case coverage.

The Digital Analytics department uses the Adobe Experience Cloud to implement personalized user experiences. The goal is to increase conversion rates and improve the customer experience through targeted personalization and testing. The technical implementation is carried out independently by specialized consultants. - A central part of the tasks includes maintaining the existing implementation within the Adobe Experience Platform. This specifically involves monitoring the data and troubleshooting the source connectors. - As part of preparing new features for use in the Adobe Experience Platform, requirements and data are first translated into Adobe's Experience Data Model. This includes creating entity-relationship diagrams (ERDs) and contextualizing the relevant data. - Building on this, the corresponding schemas are set up within the platform and datasets are prepared for further use. - Other activities include designing and setting up both new activation channels and additional data sources. - In addition, new business-relevant use cases are developed across the various phases of the customer journey to strategically increase business value. - Creating segments and performing error analysis using targeted SQL queries. - Advising on all newly introduced processing activities, on compliance with applicable data protection regulations, the required internal approval processes, as well as on documenting the legal and technical specifics.

For an AI lab we are looking for German-speaking dentists to train an AI model (Large Language Model - LLM). As a consultant, you may be invited to take part in online projects to train the model in your domain of expertise. This flexible role accommodates both experts seeking part-time engagement (minimum few hours/week) and those interested in full-time opportunities. Although every project is unique, you might typically: - Collaborate with the AI lab to provide domain-specific knowledge in dentistry. - Participate in online training sessions to enhance the AI model's understanding. - Review and validate AI-generated content for accuracy and relevance. - Offer insights and feedback to improve the model's performance. - Engage in flexible project-based work, adapting to unique project requirements.