1305 English-speaking jobs in Bavaria

System Administrator for Microsoft M365 and D365 environments. Responsibilities include operating and developing hybrid M365, ensuring security and compliance, migrating on-premises systems to the cloud, and supporting IT colleagues. Requires several years of experience in hybrid M365 administration and knowledge of Exchange, SharePoint, Teams, OneDrive, Azure AD/Entra ID. Experience with MS Dynamics 365 Finance and Supply Chain Management is a plus.

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.

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.

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.

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.

Design end-to-end AI and data architectures for vehicles, focusing on edge computing and diverse use cases. Build scalable AI software platforms and define interfaces for application development.

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.

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

Responsible for identifying market trends and new technologies for SAP application management services and cloud solutions. Designs global managed services offerings and supports sales and presales teams. Maintains product documentation and provides product knowledge to internal teams. Requires a degree in (business) information technology, economics, or a comparable field and 3-5 years of experience in SAP AMS. Fluency in English and/or German is required. Occasional travel is expected.

Validation Engineer will build and operate cloud-based validation environments for a multi-agent AI system. Responsibilities include designing AI-assisted exploration strategies, developing coverage models and metrics, establishing validation methodologies, and building observability tooling.

Regional Delivery Assurance Manager (f/m/d) will manage 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, and fluency in English.

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.

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

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 techniques. Implements and executes complete training, evaluation, and release cycles for ADAS AI models.

Builds and maintains end-to-end ML pipelines, including data ingestion, training, evaluation, and deployment. Engineers petabyte-scale data pipelines for training models. Develops tooling for efficient data processing and integration with dataset management platforms. Manages experiment tracking, hyperparameter tuning, and model registry. Develops and maintains model compilation pipelines for in-vehicle hardware. Operates observability stacks for monitoring and alerting.

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.

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

Regional Delivery Assurance Manager (f/m/d) will manage 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, and fluency in English.

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.

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.