Research Engineer for Scaling of Large Time-Series Models (f/m/div.)

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our promise to our associates is rock-solid: We grow together, we enjoy our work, and we inspire each other. Welcome to Bosch.

The Robert Bosch GmbH is looking forward to your application!

At Bosch, we are on a mission to harness the power of large-scale time-series data to optimize industrial processes and create innovative solutions. We are building the next generation of foundation models for time-series to be utilized across the various fields of the Bosch group, such as manufacturing, mobility solutions, energy systems, and IoT applications.

• As part of our team, you'll help push the state-of-the-art in model scalability by contributing to the core systems for our products.
• As a Research Engineer at Bosch, you will focus on the efficient implementation of scalable architectures for large-scale time-series models. Your primary responsibility will be to optimize training and inference pipelines, enhancing their performance in terms of runtime and memory usage.
• You will work on applying and refining these scaled models for a diverse array of industrial use cases, leveraging massive datasets from Bosch's proprietary sources to solve real-world challenges.
• The design and optimization of training and inference pipelines for time-series foundation models will be your responsibility.
• With foresight and precision, you will develop efficient algorithms for processing and analyzing massive industrial datasets.
• You will research and develop scalable architectures for large-scale time-series modeling in an industrial environment, aiming to set new standards.
• Continuously, you will drive the performance optimization and benchmarking of time-series models to ensure maximum efficiency.
• In close collaboration with engineering teams and business units, you will implement and deploy scalable solutions for industrial time-series applications.
• Your research results will be published and patented, securing and sharing our technological advantage.

• ​​​​​​Education: completed Master's degree in Computer Science, Mathematics, Physics, Technical Cybernetics, or a related field, supplemented by a PhD in Machine Learning or a machine-related field
• Experience and Knowledge:
• • demonstrated proficiency in scalable machine learning architectures and distributed training (including multi-GPU/multi-node training)
• several years of experience in AI projects focused on large-scale time-series data from industrial domains (sensors, physical systems, IoT devices, simulations, etc.)
• proven ability to translate theoretical methods into practical, high-quality code for scalable machine learning
• profound experience in large-scale data processing in an industrial environment
• excellent knowledge of MLOps (e.g. CI/CD pipelines, experiment tracking, containerization) in industrial setting
• fluent in statistical methods including time-series analysis, scalability optimization, and the ability to translate theoretical methods into solutions for concrete engineering problems
• proven ability in software implementations of large-scale algorithms in Python/Pytorch as well as to train and fine-tune foundation models and large-language models is a plus

• Personality and Working Practice: you effectively communicate complex research results and collaborate seamlessly in cross-functional teams
• Languages: very good written and spoken English, German is a plus

https://www.bosch-ai.com 

www.bosch.com/research

Please submit all relevant documents (CV, certificates, and links to GitHub or kaggle account).

We offer flexible working models: from various part-time options to mobile working and job sharing. Feel free to contact us.

Diversity and inclusion are not just trends for us but are firmly anchored in our corporate culture. Therefore, we welcome all applications, regardless of gender, age, disability, religion, ethnic origin or sexual identity.

Need support during your application?

Meltem Arabacioglu (Human Resources)

+49 174 174 4961

Need further information about the job?

Duy Nguyen-Tuong (Functional Department)

+49 711 811 49408