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.

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 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.

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

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.

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.

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 mathematicians with python experience to train an AI model (Large Language Model - LLM). 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. 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.

- Product and web development in a data-driven environment - Shaping the software architecture for new data products - Collaborating in interdisciplinary teams (e.g., with data scientists and business developers)

For an AI lab we are looking for Java 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 - 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 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 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

To replace the consent layers on the web for our international brands that were previously provided by third-party CMPs, we need to reimplement these layers so they can be operated and delivered in-house. This requires solid knowledge in Typescript, Vue.js and classic web technologies (HTML and CSS). The goal is to deliver executable code that implements all requirements and includes automated tests to verify correct functionality. What exactly is the scope of the assignment: The main focus is on developing elements for decision-making on the approach and on implementing measures along the designed project course. This specifically includes the following work packages: - Implementation of code - Implementation of executable tests that must pass for delivery, test coverage >= 80% - Creation of code documentation - 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. - Adding new brand-specific CSS themes (variable values, logos, etc.). - Incorporation of the required official IAB GVL translations (ES, FR) into 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 execution: - The desired result should be written in Typescript and Vue.js, built with Vite, tested with Vitest.

For an AI lab we are looking for AI Agent Evaluation Analyst 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 - 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.

- Independent troubleshooting and sustainable error resolution - Performing tasks for preventive maintenance - Servicing and maintaining machines and automated production systems with the latest technology - Documenting completed work - Continuously optimizing our systems and processes - Openness to and appreciation for your suggestions and ideas

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.

The Digital Analytics department uses Adobe Experience Cloud to deliver personalized user experiences. The goal is to increase conversion rates and improve customer experience through targeted personalization and testing. The technical implementation is handled independently by specialized consultants. - A core part of the tasks includes maintaining the existing implementation within the Adobe Experience Platform. This particularly involves monitoring the data and troubleshooting 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. - Based on that, the corresponding schemas are created within the platform and datasets are prepared for further use. - Further 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 specifically increase business value. - Creating segments and performing error analyses using targeted SQL queries. - Consulting on all newly introduced processing activities, covering compliance with applicable data protection regulations, the required internal approval processes, as well as documenting legal and technical specifics.

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.

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 are looking for a Freelance Agent Evaluation Analyst to take ownership of quality, structure, and insight across the project. This role goes far beyond task-checking - it’s about critical thinking, systems-level analysis, and ensuring clarity, reliability, and consistency at scale. You’ll work as both a hands-on evaluator and an analyst, collaborating with domain experts, delivery managers, and engineers. Beyond reviewing outputs, you’ll be expected to understand the “why” behind the work, identify logical gaps or inconsistencies, and propose meaningful improvements. This is a flexible, impact-driven role where you’ll have space to grow, contribute ideas, and help shape how evaluation and quality are scaled across the project. This role is especially well-suited for: Analysts, researchers, or consultants with strong structuring and reasoning skills Junior product managers or strategists curious about AI and evaluation work Smart problem-solvers (students or early-career professionals) who enjoy digging into logic, systems, and edge cases You do not need a coding background. What matters most is curiosity, intellectual rigor, and the ability to evaluate complex setups with precision. What you’ll be doing - Fully own the QA pipeline for agent evaluation tasks; - Review and validate tasks and golden paths created by scenario writers and experts; - Spot logical inconsistencies, vague requirements, hidden risks, and unrealistic assumptions; - Provide structured feedback and ensure quality alignment across contributors; Train, onboard, and mentor new QA team members; - Collaborate with domain experts, delivery managers, and engineers to improve test clarity and coverage; - Maintain and improve QA checklists, SOPs, and review guidelines; - Contribute to test planning, prioritization, and quality benchmarks; - Take initiative to suggest new approaches, tools, and processes that help scale validation and analysis.