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.