Internship in the field of Machine Learning Engineer from September 2024 Full-time

Aufgaben Sindelfingen has been at the heart of the automotive revolution since 1919, as the birthplace of the world-famous S-Class and E-Class. In the “Innovation & Digitalization” team, we not only define the future of logistics, but also set standards for driverless transport systems and state-of-the-art equipment. Our spectrum ranges from the initial idea sketch to active support during implementation

Our approach? Individual, innovative solutions for each of our plants, always hand in hand with our logistics partners. We benefit from collaboration with experts in quality management, occupational safety, assembly and IT
Thanks to the latest technologies, we are immersed in a sea of data. We use this real-time information to develop microservice-based software solutions that enable live tracking, early warning systems, error analyses and simulations. For us, transparency for all parties involved is paramount

These are some of the challenges you will face:

• A passionate team in a dynamic environment that gives you the freedom to discover new things, take responsibility and go beyond your limits
• An innovative working environment that is characterized by advanced technologies and in which you work closely with experts in the field
• The chance to experience first-hand how the most sought-after cars are created in the car factory of the future
• You will be part of a highly specialized team that deals intensively with the application and development of AI solutions in production
• Your main task will be the development and fine-tuning of machine learning models for processing multidimensional data structures and predicting temporal series
• In collaboration with other experts, you will be responsible for transforming prototypes into scalable, production-ready solutions
• The continuous exploration of the latest research results, especially in the field of time series prediction and image processing, is part of your daily business

Qualifikationen

• Degree in computer science, data science, artificial intelligence or a comparable subject area
• Confident written and spoken German and English skills
• Advanced programming skills in Python, including experience with libraries such as TensorFlow, Keras and PyTorch
• Confident handling of specialized libraries for machine learning, especially in the area of time series forecasting desirable
• Deep understanding of neural network architectures, including CNNs, RNNs, LSTM
• Expertise in the application and optimization of machine learning models for time series forecasting
• Experience with data processing tools such as Pandas, Numpy and Apache Spark
• Knowledge of MLflow for managing the machine learning lifecycle
• Familiarity with containerization and orchestration technologies such as Docker and Kubernetes
• Confident with version control systems such as Git
• Ability to critically analyze research literature and integrate the latest findings into practice
• Strong problem-solving skills, analytical mindset and the ability to recognize and communicate complex relationships
• Commitment and ability to work in a team

Additional information:
Of course, we can’t do without formalities. Please apply online only and attach a CV, current certificate of enrollment stating the semester of study, current transcript of records, relevant certificates, proof of mandatory internship if applicable and proof of the standard period of study (max. total size of attachments 5 MB) to your application and mark your application documents as “relevant for this application” in the online form
Further information on the recruitment criteria can be found”here”
If you are a national of a country outside the European Economic Area, please send us your residence/work permit
We particularly welcome online applications from severely disabled persons and persons with equivalent disabilities. If you have any questions, you can also contact the site’s representative for severely disabled employees at sbv-sindelfingen@mercedes-benz.com, who will be happy to support you in the further application process after your application
Please understand that we no longer accept paper applications and that there is no entitlement to return postage
If you have any questions about the application process, please contact HR Services by e-mail at myhrservice@mercedes-benz.com or by phone: 0711/17-99000 (Monday to Friday between 10 a.m. – 12 p.m. and 1 p.m. – 3 p.m.)