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 drive the Data & AI transformation of the BMW Group with innovative platforms, state-of-the-art cloud architecture, and excellent engineering. Together, we build the technical foundation for scalable, secure, and efficient AI solutions across the company.
As a Senior AI & Data Platform Engineer with a strong focus on semantic data, ontologies, and knowledge graphs, you play a key role in BMW’s AI transformation. You combine hands-on engineering excellence with architectural and economic ownership, ensuring that AI systems and platforms are scalable, performant, safe, stable, and cost-efficient
What awaits you?
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You develop and operate scalable, secure, and high-performance AI platforms in modern cloud environments.
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You automate infrastructure, deployments, and workflows using modern DevOps and MLOps approaches (e.g., Terraform, GitHub Actions, SonarQube).
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In addition you work closely with data scientists, software engineers, and architects to design and implement a Semantic Data Layer for BMW as the foundation for scalable, explainable, and reusable AI solutions.
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In addition, you improve AI agent and system outcomes by applying ontologies and semantic context, contributing concepts and ideas from discovery to implementation.
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You ensure platform quality, stability, and security, including monitoring, observability, logging, compliance, and documentation.
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Moreover, you engage in the BMW AI Community, share best practices, and promote a positive developer experience.
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You evaluate new technological trends and actively contribute your expertise to the further development of our AI landscape.
What should you bring along?
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University degree in computer science, mathematics, or a comparable qualification with a strong IT focus.
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At least 5 years of experience in software or platform engineering, ideally in a cloud environment (AWS or Azure) and strong experience with graph databases and semantic technologies.
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Solid expertise in ontologies, knowledge graphs, and semantic data modeling.
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Experience in building and operating enterprise-wide data platforms with a focus on scalability, performance, and user experience.
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Practical experience in machine learning or generative AI (e.g., Jupyter, PyTorch, TensorFlow, SageMaker, LangChain, Haystack), along with knowledge of modern programming languages (Python, Java, or Go) and API technologies.
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Deep understanding of IT security, data protection, and compliance requirements.
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Very good English skills; German skills are an advantage.
Would you like to help drive the Data & AI transformation at BMW Group? Apply now!
Note: Please apply exclusively online via our career portal. Applications through other channels (especially email) cannot be considered.
What do we offer?
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Challenging projects with which we are shaping the mobility of tomorrow together.
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Wide range of personal and professional development opportunities.
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Attractive, fair and performance-related remuneration.
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High level of job security.
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Annual special payments such as vacation pay, Christmas bonus, and profit sharing.
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Flexible working hours including 6 weeks annual leave and overtime compensation.
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Discounted BMW & MINI conditions.
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Many other benefits at bmw.jobs/benefits
Start date: from now on
Type of employment: unlimited
Working hours: full-time
If you apply, the next stages of the recruiting process include online testing, a pre-recorded video interview and then an interview with the hiring manager (either virtual or in person).
You can find helpful tips on your application and the application process.
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.
