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.

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: - Develop and optimize Python scripts for automation and AI tasks. - Handle and analyze large datasets efficiently. - Improve and refine AI-generated content for accuracy and quality. - Format and troubleshoot technical workflows to ensure smooth operations. - Collaborate with cross-functional teams to enhance AI tools and processes.

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 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.

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.

For an AI lab we are looking for a Ruby 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 join online projects to train the model in your area of expertise. This flexible role suits both experts seeking part-time work (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 (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 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 area of expertise. This flexible role suits both experts seeking part-time engagement (at least a few hours per 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

For an AI lab we are looking for Rust 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 - Following project-specific rubrics and requirements - Collaborating with project leads, solution engineers, and supply managers on complex or experimental projects

The Digital Analytics department uses the Adobe Experience Cloud to deliver personalized user experiences. The goal is to boost conversion rates and improve the customer experience through targeted personalization and testing. Technical implementation is handled independently by specialized consultants. - Designing and technically implementing personalized user experiences with Adobe Target - Implementing A/B and multivariate tests, including quality assurance in live environments - Integrating Adobe Target into complex system landscapes with Adobe Experience Platform and Adobe Experience Manager - Developing targeting logic based on segments, real-time data and user behavior - Advising on new features and best practices within the Adobe Experience Cloud - Preparing technical decision papers to advance the personalization strategy - Documenting and handing over the developed solutions in Confluence and similar tools - Preparing technical documentation for data protection, especially data flow diagrams - Advising on GDPR-compliant use of Adobe Target and related systems - Conducting workshops to introduce Adobe Target

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.

For replacing the consent layers currently provided by third-party CMPs on the web for our international brands, these layers will be newly implemented so they can be operated and delivered in-house. This requires solid knowledge of TypeScript, Vue.js and classic web presentation techniques (HTML and CSS). The goal is to deliver executable code that implements all requirements and includes automated tests that verify correct functionality. What exactly is the scope of the engagement: The main focus is on developing elements to decide on the approach and implementing measures along the designed project course. This specifically includes the following deliverables: - Implementation of code - Implementation of executable tests that must pass for delivery, test coverage >= 80% - Creation of documentation for the code - Creation of brand-specific cmp-config files - Creation of a project (including requirements for asset management) as a copy of the Consent Management Platform - Removal of netID references - Creation of brand-specific settings and files for custom purposes/providers - Addition of new brand-specific CSS themes (variable values, logos, etc.) - Inclusion of required official IAB GVL translations (ES, FR) in the weekly sync with the GVL - Implementation of I18n and preparation of brand-specific data sources - Implementation of PMC2.0 backend usage modules - Implementation of 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.

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.

- Product and web development in the data-driven area - 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 Kotlin 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

The service is requested as part of the Brand Image Pool Photo Shoot project. The project includes: - Managing sub-tasks throughout the entire Image Pool shoot project from January to June - Taking on brand guardianship tasks during the pool shoot project period - Detailed service description without personal reference: - Independently defining, managing, and executing the project. This ranges from project management to creating roadmaps and project presentations - Developing ideas and concepts for measures - Active management of project risks - Active management of project issues, including expert advice on escalations - Preparing and following up on stakeholder and steering board meetings - Defining the project scope and the overarching project phases - Providing transparent and appropriate information to the client regarding scope, quality, timeline, budget, and status

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.

For our client we are looking for a Korean speaking AI consultant: 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. Responsibilities: - Carefully review provided data (text, images, or videos). - Review tasks submitted by the developer team and ensure quality assurance/quality control. - Label or classify content based on project guidelines. - Identify and flag factually incorrect, sensitive, inappropriate, or unclear material.

For an AI studio we are looking for a Spanish speaking data annotation specialist: Annotation is what helps AI make sense of the world. As a QA Annotator, you may be invited to take part in online projects such as rating AI-generated content, evaluating factual accuracy, or comparing responses — when projects are available. This flexible role accommodates both experts seeking part-time engagement (minimum few hours/week) and those interested in full-time opportunities Responsibilities: - Carefully review provided data (text, images, or videos). - Review tasks submitted by the Annotators team and ensure quality assurance/quality control. - Label or classify content based on project guidelines. - Identify and flag factually incorrect, sensitive, inappropriate, or unclear material.

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