Senior Embedded AI Developer (f/m/x)

INNOVATION IS IMAGINING WHAT NO ONE ELSE CAN.

At the BMW Group, everything starts with passion. It turns a profession into a vocation. It drives us to keep reinventing mobility and bring innovative ideas onto the roads. Enthusiasm for joint projects turns a team into a strong unit where every opinion is valued. It is only when expertise, highly professional processes and enjoyment of work unite that we can shape the future together.

We are shaping AI transformation at the BMW Group and delivering highly advanced applications that enable outstanding customer experience in automated driving and intelligent vehicles. To achieve cost and energy efficient solutions, we combine deep expertise in AI and chip design, developing tailor made AI models for connected vehicles worldwide - delivering maximum performance while making optimal use of available hardware. At the intersection of semiconductors and AI, new challenges are emerging in the automotive industry.

What awaits you?

• You own the full lifecycle of machine learning models - from initial concept and experimentation through training and validation to reliable deployment on production-grade automotive systems.
• Furthermore, you optimise AI models for embedded platforms, driving performance analysis and benchmarking, as well as runtime, compute, and memory efficiency on next-generation edge hardware.
• You apply state-of-the-art compression techniques (quantisation, pruning, distillation, sparsity) to enable high-performance AI under strict real-time, energy, and hardware constraints.
• Additionally, you collaborate closely with software, machine learning, and semiconductor specialists to advance hardware/software co-design, ensuring functional correctness, safety, and deterministic real-time behaviour.
• You stay abreast of cutting-edge machine learning research and selectively translate promising developments into robust, scalable industrial applications on advanced automotive hardware.
• You design and operate scalable, MLOps-driven optimisation pipelines, enabling training, deployment, and inference across diverse embedded targets and accelerator architectures.