Data & AI Engineer - Ontologies & Knowledge Graphs (f/m/x)

Referenznummer: 26784_173199

Standort: München, BY, DE, 80809

Unternehmen: BMW Group

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 actively driving the AI transformation as part of BMW Group IT. Our team of strategists, architects, and developers shape the data and AI platform of the future and implement innovative projects with focus on value for customers and the organization.

What awaits you?

• You will contribute to selected areas of the design and continuous development of our data and AI platforms, supporting the journey from concept to productive operation.
• Together with experienced colleagues, you will support business units and IT teams with the development and implementation of data and AI use cases, gaining insights into strategy and architecture topics.
• You will apply your knowledge of ontologies, knowledge graphs, and semantic data modeling, and help integrate these into existing platforms and applications.
• Further, you will implement individual components of lighthouse use cases, such as data pipelines, semantic models, or graph structures, and learn how they are embedded into operational IT environments.
• In addition, you will contribute to platform and application development, defining interfaces, and ensuring that new requirements are reflected in our AI and data platforms.
• You will also focus on data quality, security, and compliance concepts within your area of responsibility.

What should you bring along?

• A completed Master’s degree or higher in (Business) Informatics, Computer Science, Data Science, or a comparable field with a focus on data or AI.
• Initial practical experience (e.g. internships, working student roles, thesis projects, or first professional experience) in data platforms, AI, or software development preferred.
• Knowledge of ontologies, graph databases, and/or semantic data processing, as well as a strong interest in applying this knowledge to productive environments.
• A basic understanding of cloud and platform architectures and motivation to learn about scalable data and AI solutions.
• Interest in topics such as data integration, data quality, metadata, governance, security, and data protection.
• Strong analytical thinking, curiosity, and a willingness to learn and experiment with new technologies.
• Business fluent German and English language skills.

Are you ready to drive the AI transformation at BMW with us? Apply now!

Find out more about Artificial Intelligence at the BMW Group here.

Note: Please apply exclusively online via our career portal. Applications via other channels (esp. e-mail) 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

Start date: from now on

Type of employment: unlimited
Working hours: FULLTIME

If you apply, the next stages of the recruiting process include an online test followed by interviews with the hiring manager (either virtually or in person).

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 more here.