Stellenreferenz: 188612


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INNOVATION IS IMAGINING WHAT NO ONE ELSE CAN.

Artificial Intelligence and machine learning are at the cutting edge when it comes to shaping next-gen mobility in areas like automated driving. But it takes real intellectual leadership and expertise to identify and then harness the AI trends and technologies that will transform the way people travel for good.

At BMW’s Autonomous Driving Campus, we develop and scale next-generation perception and planning systems for autonomous driving. You will build production-grade machine learning solutions using one of the industry’s largest real-world driving datasets, powering millions of vehicles worldwide.


What awaits you?

- You design and develop next-generation architecture at the intersection of multi-modal perception, foundation models, behavior learning, and end-to-end autonomous driving.
- Furthermore, you co-design cutting-edge software that translates state-of-the-art research into production-ready systems at scale.
- You execute training and evaluation cycles on large-scale datasets, from data curation and representation learning to error diagnosis and model optimization.
- Additionally, you drive the integration of backbone and foundation models into BMW's autonomous driving perception and planning stack, ensuring robustness across diverse markets and operational design domains.
- You evaluate and advance state-of-the-art methods in self-supervised learning, multi-modal fusion, and end-to-end architectures for real-world deployment.
- Furthermore, you contribute across the full development lifecycle, from early-stage research prototyping to series release, with direct impact on customers worldwide.


What should you bring along?

- University degree in Computer Science, Data Science, Machine Learning, Mathematics, Physics, or comparable qualifications.
- Several years of hands-on experience in ML model development for perception, autonomous driving, or comparable vision systems, ideally in an industry setting.
- Strong knowledge of current state-of-the-art approaches in autonomous driving perception, end-to-end architectures, and foundation or backbone model architectures.
-  Proven production experience with machine-learning frameworks such as PyTorch or TensorFlow, including training on large-scale datasets and programming skills in Python or C++.
- Demonstrated ownership in a mature AD/ADAS, robotics, or large-scale autonomy stack, with measurable delivery impact.
- Deep expertise in large-scale model development, including training, evaluation, error analysis, and optimisation across different ODDs and markets; experience in safety-critical or regulated environments is a plus.
- A visionary mindset with the ability to anticipate trends, challenge conventions, and drive architectural decisions for next-generation autonomous driving systems.


Ready to build the end-to-end driving systems that will power the world's next generation of autonomous vehicles? Apply now!

Note: Please apply exclusively online via our career portal. Applications through other channels (especially email) cannot be considered.


What do we offer?

- Challenging projects with which we are shaping the mobility of tomorrow together.
- Wide range of personal and professional development opportunities.
- Attractive, fair and performance-related remuneration.
- High level of job security.
- Annual special payments such as vacation pay, Christmas bonus, and profit sharing.
- Flexible working hours including 6 weeks annual leave and overtime compensation.
- Discounted BMW & MINI conditions.
- Many other benefits at  bmw.jobs/benefits


If you apply, the next stages of the recruiting process include online testing and then an interview with the hiring manager (either virtual or in person).


Find out more about Artificial Intelligence at the BMW Grouphere .


You can find helpful tips on your application and the application process here .


At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants. Learn morehere .