Principal Vehicle AI Architect Research

Principal Vehicle AI Architect Research

BMW Group

Munich, Germany

What awaits you?

• You design end-to-end AI and data architectures for future vehicle generations, focusing on the latest AI trends;
• Additionally, you build architectural concepts that cover diverse use cases, such as digital cockpit and driver interaction for holistic customer experiences;
• You provide architectural guardrails to business units and development teams, enabling competitive AI products on our platforms;
• Furthermore, you drive the implementation of scalable AI software platforms using state-of-the-art AI research and leveraging our in-house software stacks;
• Moreover, you link platform and application development by defining interfaces and ensuring that new AI trends and requirements are integrated directly into the AI and data platforms;
• You co-create and prioritise AI use cases across domains, assess feasibility and value, and translate them into system and hardware requirements;
• Beyond that, you continuously evaluate the latest AI developments and implement them where they add value.

What should you bring along?

• University degree (Master’s or PhD) in AI, Machine Learning, Data Science, Computer Science or related field;
• Several years of experience in AI/data architecture; experience in automotive E/E and vehicle AI is a plus;
• Proven track record in embedded AI architectures and implementation of Small Language Models (SLM) and Vision-Language Models (VLM);
• Proficiency in AI training workflows and model optimisation for deployment, such as pruning, fine-tuning, quantization and multimodal encoding is a plus;
• Familiarity with open-source AI stacks (e.g., vLLM, llama.cpp, ONNX Runtime, TensorRT, LiteRT LM, ExecuTorch, Llama-Stack) on embedded hardware (NPU) and comparison to proprietary frameworks with focus on latency, throughput, and energy;
• Solid software development and engineering skills: Python, API technologies, CI/CD, and cloud-native deployment;
• Leadership experience in agile, cross-functional teams and expertise in multi-agent orchestration and conversation-based workflows.