About the job
At Bosch, we are pioneers of innovation, dedicated to shaping the future of intelligent systems that are efficient, safe, and improve lives worldwide. We are looking for a forward-thinking Research Engineer to join our vibrant team, specializing in the dynamic intersection of reinforcement learning (RL) and agentic AI. Your innovative contributions will significantly influence critical Bosch sectors, such as automated driving, smart home solutions, energy management, and advanced manufacturing. As an integral part of our team, you will elevate the capabilities of AI technology, spearheading foundational research and developing core systems that will directly enhance Bosch's product offerings. Join us in converting complex challenges into tangible solutions.
- In this role, you will lead the design and architecture of cutting-edge AI systems, focusing on the seamless integration of reinforcement learning with agentic AI systems and multi-modal foundational models.
- Your responsibilities will include training and fine-tuning multi-modal large models to ensure their behavior aligns with Bosch's product specifications and real-world applications.
- You will push the boundaries of AI by improving existing machine learning frameworks and integrating innovative data-driven, generative techniques with secure, scalable reinforcement learning methodologies.
- A major component of your work will involve conducting original research, leading impactful projects that address complex scientific and practical issues at the intersection of RL and agentic AI, thereby making a significant contribution to Bosch's product line.
- Collaboration will be essential, as you will work closely with internal stakeholders and product teams to thoroughly understand their needs, conceptualize groundbreaking solutions, and deliver high-quality Minimum Viable Products (MVPs).
- Additionally, you will have the opportunity to share your insights by publishing and presenting your research findings in top-tier academic forums, while actively contributing to the larger scientific community.
