Research Engineer - Reinforcement Learning and Agentic AI (f/m/div.)

At Bosch, we are at the forefront of innovation, shaping the future of intelligent systems that are efficient, safe, and enhance lives globally. We are seeking a visionary research engineer to join our dynamic team, focusing on the powerful intersection of reinforcement learning (RL) and agentic AI. Your groundbreaking work will directly impact critical Bosch domains, including automated driving, smart home systems and energy management, advanced and flexible manufacturing. As a key contributor, you will redefine the state-of-the-art in AI capabilities, driving foundational research and building core systems that directly shape Bosch's product portfolio. Join us in transforming complex challenges into real-world impact.

• As a research engineer, you will be at the forefront of pioneering system design, with the responsibility to architect, develop, and deploy sophisticated AI systems that seamlessly integrate reinforcement learning with agentic AI systems and multi-modal foundation models.
• In your role, you will involve training and fine-tuning multi-modal large models to precisely align their behaviors with Bosch product requirements and use cases.
• You will be expected to advance AI paradigms by enhancing existing machine learning systems, integrating cutting-edge data-driven, generative approaches with robust, safe, and scalable reinforcement learning algorithms.
• A significant part of your work will be to conduct original research, leading high-impact projects to solve challenging scientific and applied problems at the confluence of RL and agentic AI, making a real impact on Bosch products.
• Strategic collaboration is key, and you will partner closely with internal customers and product teams to deeply understand requirements, conceptualize innovative solutions, and deliver high-quality Minimum Viable Products (MVPs).
• Furthermore, you will have the opportunity to disseminate knowledge by publishing and presenting groundbreaking research findings in premier academic venues and actively contributing to the broader scientific community.