446 English-speaking jobs in Munich

Develop and operate AI platforms for data pipelines, training, deployment, and inference. Optimize AI models and lead technical solutions for scalable AI platform features. Ensure reliability, performance, and cost-efficient operation of AI-based systems.

The Deutsches Museum seeks an IT Systems Engineer / IT Specialist for System Integration to manage and modernize network infrastructure. Responsibilities include network design, operation, troubleshooting, and support, as well as transitioning to cloud technologies.

Develop and optimize embedded machine learning models for connected vehicles. Own the full lifecycle of models from concept to production deployment. Apply state-of-the-art compression techniques and collaborate with software and hardware specialists.

Define AI system strategy for ADAS, including model architectures, data flows, and integration concepts. Develop prototypes, evaluation pipelines, and data models, ensuring they meet real-world product requirements. Collaborate with expert teams to create cutting-edge ADAS products spanning L2 to L4 autonomous driving.

Develop and industrialize end-to-end machine learning algorithms for ADAS functions. Design and improve human-like driving behavior using behavior models, reinforcement learning, and hybrid data- and model-driven approaches.

As a Senior AI Platform Security Engineer, you will define architecture standards, security policies, and SLAs/SLOs for an AI Moderation Layer. You will lead the design of a multi-layered defense strategy to protect against AI threats and establish and improve the security lifecycle for LLMs/Agents. You will collaborate with legal, compliance, and data protection teams to ensure regulatory alignment for AI security. You will also mentor and guide an agile team of engineers and data scientists.

Senior Applied AI/ML Application Engineer will build, prototype, and deliver use cases leveraging edge device models for the BMW Intelligent Personal Assistant. Responsibilities include integrating models, prototyping GenAI experiences, collaborating with model engineering, and building evaluation tools. Requires a university degree in a related field, at least five years of application engineering experience, and strong Python and Java/Kotlin skills.

Designs, builds, and manages Kubernetes clusters on AWS EKS for autonomous driving AI/ML workloads. Provisions and orchestrates large-scale GPU clusters for distributed AI/ML training and experimentation. Implements and automates CI/CD pipelines for AI/ML workflows. Develops and maintains infrastructure components tailored to autonomous driving data. Collaborates with data scientists, AI/ML engineers, and cloud architects.

Act as a financial business partner for the Dairy Category, providing insights and driving data-driven decisions. Ensure accurate month-end closings, own the forecasting process, and support finance transformation.

Senior Analyst to design, evolve, and maintain group-wide price forecasting methodologies and standards. Responsibilities include model review, market analysis, and stakeholder management. Requires a Master's degree in a quantitative field, 5-7+ years of experience in energy markets, and strong Python and communication skills.

Senior Analyst will design, evolve, and maintain group-wide price forecasting methodologies. Responsibilities include model review, validation, market analysis, and stakeholder management. Requires a Master's degree in a quantitative field, 5-7+ years of experience in energy markets, and strong Python and communication skills.

Regional Delivery Assurance Manager will implement and execute delivery assurance processes for selected consulting projects, including risk reviews, risk assessments, and quality assurance reviews. The role requires 5+ years of experience in SAP project delivery, 3+ years in risk management and quality assurance, strong communication and stakeholder management skills, and the ability to work autonomously. Willingness to travel 20-40% is required.

Identifies and evaluates market trends for IaaS and PaaS services for SAP customers. Creates managed services portfolio roadmaps and designs new global managed cloud services. Manages end-to-end service offers and supports sales and presales teams.

Develop and operate scalable AI platforms in cloud environments. Support the entire AI lifecycle, from data preparation to deployment. Automate infrastructure and workflows using DevOps and MLOps tools. Collaborate with data scientists and engineers to design and implement platform functionalities. Ensure platform quality, stability, and security.

As a Senior AI Platform Security Engineer, you will define architecture standards, security policies, and SLAs/SLOs for an AI Moderation Layer. You will lead the design of a multi-layered defense strategy to protect against AI threats and establish and improve the security lifecycle for LLMs/Agents. You will collaborate with legal, compliance, and data protection teams to ensure regulatory alignment for AI security. You will also mentor and guide an agile team of engineers and data scientists, fostering best practices in architecture, security, and platform engineering.

Designs end-to-end AI and data architectures for future vehicle generations, focusing on AI trends. Builds architectural concepts for diverse use cases, such as digital cockpits and driver interaction. Provides architectural guidance to business units and development teams. Drives the implementation of scalable AI software platforms using state-of-the-art AI research. Co-creates and prioritizes AI use cases, assesses feasibility and value, and translates them into system and hardware requirements. Evaluates and implements the latest AI developments.

Designs and operates knowledge graphs and graph databases to capture domain knowledge and operational data. Builds context-engineering pipelines for LLM-based agents and implements feedback loops for continuous improvement. Develops ontologies and semantic models for the automotive AI domain.

Senior Applied AI/ML Engineer will select and adapt base models for voice assistant and intelligence tasks. Develops training, fine-tuning, and evaluation pipelines to refine models. Implements compression strategies for cost-efficient inference and collaborates with performance engineers on hardware-aware model variants.

Designs, builds, and manages Kubernetes clusters on AWS EKS for autonomous driving AI/ML workloads. Provisions and orchestrates large-scale GPU clusters for distributed AI/ML training and experimentation. Implements and automates CI/CD pipelines for AI/ML workflows. Develops and maintains infrastructure components tailored to autonomous driving data.

Develops end-to-end AI-based ADAS functions, including object detection, behavior prediction, and trajectory planning. Designs and optimizes humanlike driving behavior models using various learning paradigms. Implements and executes complete training, evaluation, and release cycles, ensuring data selection, scene mining, and KPI-based validation.