25 English-speaking jobs in Ingolstadt

The Validation Engineer will own the virtual validation of a multi-agent AI system, developing AI-assisted validation strategies and building cloud-based validation environments. Responsibilities include designing test architectures, scenario pipelines, and behavioral oracles, as well as developing coverage models and metrics for non-deterministic multi-agent systems. The role also involves establishing validation methodologies suited to stochastic AI behavior and building observability and diagnostics tooling.

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.

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.

Design end-to-end AI and data architectures for vehicles, focusing on edge computing and diverse use cases. Drive the implementation of scalable AI software platforms and define interfaces between platforms and applications.

Develop, implement, and operate AI/ML models for embedded automotive systems. Optimize AI models for performance, runtime, and memory efficiency on edge hardware. Collaborate with software and hardware specialists on hardware/software co-design.

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.

Builds and maintains end-to-end ML pipelines, including data ingestion, training, evaluation, and deployment. Engineers petabyte-scale data pipelines and develops tooling for efficient data processing. 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.

Develop and deliver AI-based ADAS functions, including object detection, behavior prediction, and trajectory planning. Design and optimize humanlike driving behavior models. Own complete training, evaluation, and release cycles.

Designs end-to-end AI and data architectures for future vehicles, focusing on AI trends and diverse use cases. Builds architectural concepts, provides guidance to business units, and drives the implementation of scalable AI software platforms. Evaluates AI developments and integrates them into platforms.

Build, prototype, and deliver AI/ML use cases leveraging edge device models for the BMW Intelligent Personal Assistant. Integrate models, prototype GenAI experiences, and collaborate with engineering and UX teams.

Designs the AI architecture for the AI-defined vehicle of tomorrow, integrating LLMs, VLAMs, End2End driving models, Foundation world models, and agent systems into ADAS architectures. Develops prototypes, evaluation pipelines, and data models, ensuring technical feasibility and alignment with real-world product requirements. Collaborates with expert teams to co-create cutting-edge ADAS products spanning L2 to L4 autonomous driving.

Senior Applied AI/ML Engineer develops and refines edge GenAI models for the BMW Intelligent Personal Assistant. Responsibilities include selecting and adapting base models, creating training pipelines, implementing compression strategies, and collaborating with performance engineers. Requires a university degree in a related field, experience in applied machine learning, proficiency in PyTorch and Transformers, and expertise in model compression and fine-tuning.

Network Engineer responsible for the secure and stable operation of the company's network infrastructure. Experience with CISCO and Meraki network solutions is required.

Designs, implements, and operates data solutions including DWH, BI, and big data solutions. Develops ETL processes, reporting, and dashboards. Advises management on data-driven decision-making.

Manage and support Microsoft 365 applications including Teams, SharePoint, OneDrive, Intune, and PowerApps. Provide 2nd-level support, including root cause analysis and preventive measures. Support Workplace Management, software distribution, and business applications.

Technical expert for electroacoustic safety systems. Analyze, test, explain, and improve systems. Support Engineering and Sales 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.

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.

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 SAP application management services and cloud solutions. Creates managed services portfolio roadmaps and designs new global managed services. Manages end-to-end service offers and supports sales and presales teams.