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

For replacing the Consent Layers currently provided by third-party CMPs on the web for our international brands, these layers need to be reimplemented so we can run and serve them 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 implements all requirements and includes automated tests to verify correct function. What exactly is the scope of work: The focus is on preparing decision-making elements for the approach and implementing measures along the resulting project workflow. This specifically includes the following work packages: - Implementation of code - Implementation of executable tests that must pass with test coverage >= 80% before delivery - Creation of documentation for the code - Creation of brand-specific cmp-config files. - Setting up 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.). - Including the required official IAB GVL translations (ES, FR) in the weekly sync 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 deliverable should be written in TypeScript and Vue.js, built with Vite, and tested with Vitest.

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

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 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

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.

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. - Design and technical implementation of personalized user experiences with Adobe Target - Implementation of A/B and multivariate tests, including quality assurance in live environments - Integration of Adobe Target into complex system landscapes, including Adobe Experience Platform and Adobe Experience Manager - Development of targeting logic based on segments, real-time data, and user behavior - Advice on new features and best practices within the Adobe Experience Cloud - Preparation of technical decision templates for the development of the personalization strategy - Documentation and handover of developed solutions in Confluence and similar tools - Preparation of technical materials for data protection, especially data flow diagrams - Advice on GDPR-compliant use of Adobe Target and related systems - Conducting workshops to introduce Adobe Target

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.

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 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

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

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 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

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

For our client company in the financial services sector, we are looking for a Partner Sales Manager (m/f/d). The client has commissioned us to steer a cross-departmental sales project to acquire new software distribution partners. The focus is on developing a partner sales strategy and integrating it into existing financial services solutions. Tasks: - Steering the cross-departmental sales project to acquire new distribution partners in integrated software solutions (ISV – Independent Software Vendor) - Supporting the acquisition of these strategically important partners - Developing a comprehensive software partner sales strategy and defining relevant KPIs - Managing the integrated sales together with the client's financial services solutions - Supporting the design and implementation of the software partner sales strategy - Collaborating in the development and implementation of new processes and shaping the organization

To strengthen data-driven cross & upsell as well as 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 - Advising on data flows, selections, and profiling strategies Development in PL/SQL - Implementing and optimizing data selection, transformation, and aggregation pipelines in Oracle PL/SQL - Mapping predefined business logic for customer segmentation Testing & Quality Assurance - Planning and executing unit, integration, and regression tests - Documenting test cases and results Operations & Monitoring - Monitoring running jobs and workflows (performance, error handling) - Tuning SQL queries and batch processes Communication Outputs - Connecting and supplying channels for email, SMS, outbound calls, and mail - Implementing data-driven personalization and targeting

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

The development and quality assurance of the data layer includes its complete provisioning through the respective web application. The data layer forms the central data foundation for analyzing user behavior and for personalized content during the website visit. To increase reliability and stability, automated tests should be used to significantly reduce manual regression tests. For this task, a Test Automation Engineer with a focus on Playwright (Elastic) is needed. - Development and implementation of automated end-to-end tests with the npm package @elastic/synthetics (Playwright) for data layer tests. - Analysis of existing test processes, identification and prioritization of automation potentials. - Creation, maintenance, and optimization of test scripts considering current best practices. - Integration of automated tests into existing CI/CD pipelines (e.g., Jenkins, GitHub Actions) to enable continuous test automation. - Documentation of test cases, test results, and test coverage in tools like Jira and Confluence. - Advising stakeholders on the selection and introduction of appropriate test strategies, test tools, and frameworks. - Conducting code reviews for test automation scripts to improve quality and maintainability. - Preparing decision templates and recommendations for action to further develop test automation. - Providing advice on error analysis and resolution within test automation. - Consulting on setting up reports and alerting with Elastic Observability. - Promoting traceability and reproducibility of test results.