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Stellendetails zu: Research Scientist Agentic AI, Reinforcement Learning and Neuro-Symbolic Systems (f... / REF283483D

Research Scientist Agentic AI, Reinforcement Learning and Neuro-Symbolic Systems (f... / REF283483D

Kopfbereich

Angebotsart: Arbeit
Arbeitgeber: Robert Bosch GmbH

Besondere Merkmale

Arbeitsort

Renningen

Anstellungsart

Vollzeit

Befristung

unbefristet

Beginn

ab sofort

Berufsbezeichnung

  • Machine Learning Engineer

Stellenbeschreibung

Willkommen bei Bosch

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Job Description

  • As a research scientist in the semantic understanding and reasoning group (CR/AIR4) at Bosch Corporate Research, you will lead and advance research on intelligent AI systems that are able to take action, reason over goals and constraints, as well as organize knowledge through complex neuro-symbolic structures.
  • Your work will focus on next-generation agentic systems that combine reinforcement learning, structured reasoning, memory, and knowledge-based representations to operate effectively in semantically rich also technically demanding environments.
  • This role goes beyond individual technical contributions. You will contribute to shaping Bosch's scientific agenda in this area by identifying promising research directions, initiating and coordinating research activities, building connections to external academic and industrial partners, as well as representing Bosch in relevant research communities.
  • You are expected to bring a strong external network and effectively position Bosch in collaborative projects, scientific exchanges, also strategic initiatives related to agentic AI, reinforcement learning, as well as neuro-symbolic systems.
  • From a scientific perspective, you focus on developing systems that move from passive understanding toward goal‑directed behavior. You investigate how agents learn through interaction, simulation, and structured feedback, represent also manipulate knowledge in compositional forms, as well as integrate reinforcement learning with symbolic abstractions, hierarchical planning, memory, and reasoning. Your objective is to design systems that actively act while structuring knowledge to enable robust behavior, interpretability, also strong generalization.
  • You will work closely with research scientists, engineers, students, as well as domain experts across Bosch. In addition to conducting high-level research, you will mentor students also junior researchers, actively shape and structure collaborative research activities, and contribute to the organizational development of this research area. Your work will be instrumental in establishing Bosch’s long-term leadership in intelligent systems for complex technical environments.

Qualifications

  • Education:
    excellent MSc in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Systems Engineering, or related fields
  • PhD in Machine Learning, Reinforcement Learning, Agentic AI, Neuro-Symbolic AI, Sequential Decision-Making, or a closely related area is mandatory
  • ideally several years of post-PhD research experience in academia, industry research, or a comparable environment
  • strong publication record in leading AI, machine learning, or autonomous systems venues such as NeurIPS, ICLR, ICML, AAAI, IJCAI, CoRL, RSS, AAMAS, ACL, EMNLP, KR, or similar
  • Experience and Knowledge:
    Agentic AI, RL undamp; Action‑Oriented Systems
    strong expertise in reinforcement learning and agentic AI, including sequential decision‑making and learning‑based planning
  • experience with advanced RL paradigms such as model‑based, hierarchical, offline, multi‑agent, or constrained RL
  • deep understanding of goal‑directed AI systems involving memory, tool use, planning, multi‑step reasoning, and long‑horizon behavior
  • ability to design and analyze systems that act in complex environments and improve through interaction, simulation, or structured feedback
  • Neuro‑Symbolic Systems undamp; Knowledge Organization
    proven experience in combining learning‑based AI with symbolic or structured representations
  • familiarity with neuro‑symbolic architectures, knowledge graphs, formal reasoning structures, and compositional representations
  • ability to design systems that organize knowledge in semantically meaningful ways while supporting action, planning, interpretability, and generalization
  • Systems Engineering undamp; Structured Technical Domains
    interest in applying advanced AI methods to complex technical and cyber‑physical domains such as systems engineering, robotics, or industrial automation
  • experience with structured engineering artifacts (e.g. requirements, system models, simulations, or formal specifications) is an advantage
  • ability to frame complex technical challenges in terms of sequential decision‑making, planning, or knowledge‑based reasoning
  • Scientific Leadership, Networking undamp; Mentoring
    demonstrated ability to initiate, structure, and lead research activities in a focused technical domain
  • strong external scientific network and experience building collaborations with academic and industrial partners
  • proven track record in publications, project coordination, and community‑building activities
  • mentoring experience with students and junior researchers, combined with strong organizational and coordination skills
  • AI Infrastructure undamp; Research Prototyping
    solid experience in Python and modern deep‑learning frameworks (e.g. PyTorch, TensorFlow, JAX)
  • familiarity with scalable experimentation, reproducible research, and collaborative software development
  • ability to translate research ideas into functional prototypes and experimental platforms
  • Scientific Contributions undamp; Mindset
    strong sense of ownership and entrepreneurial mindset in driving research topics
  • ability to connect fundamental research with long‑term strategic value
  • excellent analytical and communication skills, paired with a collaborative, interdisciplinary leadership style
  • Personality and Working Practice: you are a scientifically strong and organizationally capable researcher with a clear ambition to shape and lead research activities in the field of agentic AI at Bosch; you combine deep methodological expertise with external visibility, mentoring experience, and the ability to build and coordinate impactful research efforts
  • Languages: fluent English skills written and spoken, German is a plus

Additional Information

https://www.bosch-ai.com
www.bosch.com/research
Please submit all relevant documents (CV, letter of motivation, 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.
Work #LikeABosch starts here: Apply now!

Arbeitsorte

Unternehmensdarstellung: Robert Bosch GmbH

Robert Bosch GmbH

Informationen zur Bewerbung