198 English-speaking jobs in Munich

Technical AI Engineer responsible for complex, cross-functional AI initiatives from requirements analysis to implementation. Designs and develops scalable AI systems, focusing on Generative AI, and manages AI-related projects. Collaborates with internal and external partners.

Senior Machine Learning Engineer will evaluate and select GenAI models to enhance simulation performance. Develop and operate a scalable training and MLOps infrastructure, including distributed training, automated evaluation pipelines, and optimized cloud/on-prem compute usage. Optimize the GPU toolchain, scheduling, profiling, and resource allocation. Contribute to the simulation of driver assistance systems and evaluate simulation quality.

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.

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

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.

Define core semantic ontologies and context data models for autonomous driving and real-time systems. Drive the implementation of advanced data infrastructure functions and design a multi-level memory concept for vehicles. Orchestrate the integration of ML, GenAI, and symbolic reasoning rules to curate semantic context. Develop the data model strategy for fine-tuning SLMs and VLMs for agentic applications.

Integrate and prototype GenAI & ML models for the BMW Intelligent Personal Assistant. Develop new in-car intelligence features, collaborating with model engineering and UX teams. Requires a computer science or engineering degree and 5+ years of application engineering experience.

Develop and maintain an AI-supported software development ecosystem, including AI coding assistants and tools. Optimize the software development lifecycle through AI integration and evaluate new AI technologies. Collaborate with development teams to promote AI adoption and share knowledge through workshops and training.

Builds and maintains end-to-end ML pipelines, including data ingestion, training, evaluation, and deployment. Engineers petabyte-scale data pipelines, transforming raw automotive data into training formats. Develops and maintains model compilation pipelines for in-vehicle hardware. Operates observability stacks, providing dashboards, alerts, and log aggregation.

Shape future system and hardware architecture for AI applications in vehicles. Design end-to-end AI and data architectures, focusing on edge computing and diverse use cases. Drive the implementation of scalable AI software platforms using the latest technologies.

Drive the Data & AI transformation of the BMW Group by designing, implementing, and operating machine learning and generative AI solutions. You will work with data scientists, software engineers, and architects to ensure platform quality, stability, and security.

Designs the AI architecture for the AI-defined vehicle of tomorrow, defining AI system strategy for ADAS, including model architectures, data flows, and integration concepts. Develops prototypes, evaluation pipelines, and data models, testing them against real-world product requirements. Collaborates with expert teams to co-create cutting-edge ADAS products spanning L2 to L4 autonomous driving.

Senior Data Engineer / Ingenieur (Machine Learning Engineering) is needed to support the AI lifecycle, from data preparation to the operation of machine learning and generative AI solutions. Experience in building and operating enterprise-wide AI platforms, machine learning, and modern programming languages is required.

Develop and maintain a company-wide ecosystem for AI-supported software development. Optimize the software development lifecycle through AI integration. Share knowledge through hackathons, conferences, and training sessions. Collaborate with development teams to promote AI adoption.

Develop and maintain a company-wide ecosystem for AI-supported software development. Optimize the software development lifecycle through AI integration. Share knowledge through hackathons, conferences, and training sessions. Collaborate with development teams to promote AI adoption.

Shape future system and hardware architecture for AI applications within vehicles. Design end-to-end AI and data architectures, focusing on edge computing and diverse use cases. Drive the implementation of scalable AI software platforms using the latest technologies.

Senior Security Engineer responsible for defining and implementing security policies, SLAs, and global scalability for an AI Moderation Layer. Leads the design of a multi-layered defense strategy to protect against AI threats. Collaborates with legal, compliance, and data protection teams to ensure regulatory alignment. Mentors and guides a team of engineers and data scientists. Requires 8+ years of experience in software or platform security and architecture in cloud environments, deep expertise in LLM and agent security, and proven leadership in security lifecycle and compliance.

Senior Security Engineer responsible for defining architecture standards, security policies, and SLAs/SLOs for an AI Moderation Layer. Leads the design of a multi-layered defense strategy to protect against AI threats and establishes and improves the security lifecycle for LLMs/Agents. Collaborates with legal, compliance, and data protection teams to ensure regulatory alignment for AI security. Mentors and guides a team of engineers and data scientists.

Designs the AI architecture for the AI-defined vehicle of tomorrow, defining AI system strategy for ADAS, including model architectures, data flows, and integration concepts. Develops prototypes, evaluation pipelines, and data models, testing against real-world product requirements. Collaborates with expert teams to co-create cutting-edge ADAS products spanning L2 to L4 autonomous driving.

Designs and builds high-performance search and query pipelines over petabyte-scale data lakes, enabling rapid dataset assembly and model evaluation. Builds and operates indexing and cataloging systems for automotive sensor data, including metadata extraction, signal-level indexing, and embedding-based similarity search. Implements distributed compute pipelines for large-scale data evaluation and develops dataset assembly pipelines.