To strengthen data-driven cross & upsell and retention campaigns, Customer Interaction runs a platform where campaign processes, including a profiler, are developed, orchestrated, and monitored. We are looking for support in the following areas: Analysis & Consulting - Functional and technical analysis of existing campaign processes - Advice on data flows, selections, and profiling strategies PL/SQL Development - Implementation and optimization of data selection, transformation, and aggregation streams in Oracle PL/SQL - Mapping defined business logic for customer segmentation Testing & Quality Assurance - Planning and executing unit, integration, and regression tests - Documentation of test cases and results Operations & Monitoring - Monitoring running jobs and workflows (performance, error management) - Tuning SQL queries and batch processes Communication Outputs - Connecting and supplying channels such as email, SMS, outbound call, and mail - Implementing data-driven personalization and targeting

To replace the consent layers currently displayed on the web by third-party CMPs for our international brands, these layers need to be newly implemented so they can be maintained and delivered in-house. This requires solid knowledge of TypeScript, Vue.js and classic web display techniques (HTML and CSS). The goal is to deliver executable code that implements all requirements and includes automated tests that prove correct functionality. What exactly is the scope of work: The main focus is on developing elements to decide the approach and on implementing measures along the project course defined by this. This specifically includes the following service packages: - 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 treasury 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 sync with the 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, build with Vite, tests with Vitest.

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.

- Product and web development in the data-driven domain - Co-design of the software architecture for new data products - Collaboration in interdisciplinary teams (e.g. with data scientists and business developers)

- You develop modern, high-performance web frontends using React, TypeScript, HTML, and CSS - You implement responsive designs with consideration for accessibility and performance - You plan and carry out unit and integration tests (for example with Playwright) - You troubleshoot issues in development, testing, or live environments

For an AI lab, we are looking for a Rust Developer to train an AI model (Large Language Model - LLM). You will help the 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 works for both experts seeking part-time work (minimum a few hours/week) and those interested in full-time roles. - Code generation and code review - Prompt evaluation and complex data annotation - Training and evaluating 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

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.

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 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

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.

An AI Lab is seeking professionals experienced in working with tests to join their innovative team as English AI Trainers. The role involves crafting and editing texts, as well as evaluating AI-generated replies to ensure quality and accuracy. This position is ideal for individuals with expertise in writing, editing, and analyzing content, particularly in the context of AI and language models. As part of a cutting-edge AI lab, you will contribute to the development and refinement of advanced AI systems. 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: - Craft and edit high-quality texts tailored to specific requirements. - Evaluate and analyze AI-generated replies for accuracy, relevance, and quality. - Collaborate with teams to improve AI language models and content generation processes. - Provide feedback and suggestions to enhance AI performance. - Conduct research to ensure content aligns with industry standards and user expectations.

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 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 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 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.

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 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

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.

An AI lab is looking for a freelance mathematics experts to evaluate AI models. The goal of the project is to assess the performance, accuracy, and reliability of AI models applied in mathematics 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 mathematics 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.