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

Renningen, Baden-Württemberg, Germany -

Full Time

Start Date

Immediate

Expiry Date

02 Jun, 26

Salary

0.0

Posted On

04 Mar, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Reinforcement Learning, Agentic AI, Deep Reinforcement Learning, Behavioral Learning, Safe RL, Offline RL, Multi-agent RL, Large Language Models, Visual Language Models, Visual Language Action Models, Supervised Fine-Tuning, DPO, RLHF, Python, PyTorch, JAX

Industry

Software Development

Description

Unternehmensbeschreibung 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! Stellenbeschreibung 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. Qualifikationen Education: excellent PhD in Computer Science, Artificial Intelligence, Machine Learning or a related field, with a strong publication record in leading conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ACL) Experience and Expertise: comprehensive practical experience and theoretical understanding in Deep Reinforcement Learning (RL) and behavioral learning, ideally with expertise in emerging behaviors with RL, Safe RL, Offline RL, and/or Multi-agent RL proven track record with Agentic AI, Large Language Models (LLMs), Visual Language Models (VLMs), Visual Language Action Models (VLAs) including practical experience with advanced fine-tuning methods such as Supervised Fine-Tuning, DPO, and RLHF excellent knowledge of Python and profound knowledge of industry-standard Machine Learning frameworks and libraries (e.g., PyTorch, Hugging Face, JAX, TensorFlow); good knowledge of C++ and related frameworks (e.g., ROS 2) experience in software development in larger teams and the deployment of ML-based systems for real-world solutions, especially background knowledge in MLOps and CI/CD is welcome Personality and Working Style: you are able to approach complex challenges methodically and solution-oriented manner, always demonstrating high-quality standards and a strong sense of responsibility; you enjoy working in a collaborative environment and actively participate in fast-paced research and development processes; you understand AI business models and drive solutions beyond prototype status to full implementation in cooperation with business units Enthusiasm: you are enthusiastic about solving complex technical challenges and developing novel, impactful solutions in interdisciplinary teams; you are also fascinated by the synergistic potential between Reinforcement Learning and generative AI Languages: very good English skills written and spoken, German is a plus Zusätzliche Informationen 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? Michael Pfeiffer (Functional Department) +49 711 811 18195 Luigi Palmieri (Functional Department) +49 711 811 7584 Work #LikeABosch beginnt hier: Jetzt bewerben! Legal Entity: Robert Bosch GmbH

Responsibilities

The research engineer will architect, develop, and deploy sophisticated AI systems integrating reinforcement learning with agentic AI and multi-modal foundation models, focusing on training and fine-tuning large models for Bosch product requirements. Responsibilities include conducting original research, leading high-impact projects at the confluence of RL and agentic AI, and collaborating with product teams to deliver high-quality Minimum Viable Products (MVPs).