Company Description
At Bosch, we shape the future with technologies that enrich people’s lives. Join Robert Bosch Robotics GmbH as the hands-on architect of Robotics AI within our initial Industrial Robot Skills team. Define how predictive models, reasoning, executable skills and control work together, then implement and test the critical ideas on real robots. Welcome to Bosch.
The Robert Bosch GmbH is looking forward to your application!
Job Description
As part of our team, you will own the robotics AI architecture and technical hypotheses, selecting world-action and video-action models, VLA policies, embodied reasoning, or classical planning according to task, data, and execution constraints.
You will design heterogeneous systems that connect learned models with Code-as-Policy programs, Graph-as-Policy structures, and reusable skills. You specify state and action representations, interfaces, execution checks, as well as recovery behavior.
Additionally, you will implement and adapt models and agentic robot programs. You investigate predictive dynamics, imitation learning, reinforcement learning, or feedback-driven skill refinement, then justify your choices with baselines and ablations.
You will also define evaluation across simulation and physical rollouts, including held-out tasks, embodiment transfer, intervention rate, latency, recovery, and repeatability. In doing so, you distinguish first-attempt success from results achieved through retries.
Furthermore, you will collaborate closely with the deployment engineer to turn the architecture into a functioning embodiment. Together, you diagnose model, planning, or control failures and revise the design based on measured robot behavior.
Using the Agentic AI Software Factory, you will drive implementation and experiments while validating generated code and experimental conclusions. You maintain reproducible artifacts, versioned skills, and accountable release decisions.
Qualifications
Education: completed Bachelor’s or Master’s degree in Robotics, Computer Science, Machine Learning, Control Engineering or a related field
Experience and Knowledge:
substantial hands-on contributions to robotics AI systems on physical robots, with defensible architecture decisions and reproducible results
deep expertise in predictive world-/video-action modeling or agentic robot planning and Code-as-Policy, integrating learned and classical components; relevant experience may include GaP, CaP-X, or ASPIRE/ENPIRE-style feedback loops; comparable implementations are equally accepted, and mastery of every named framework is not required
proven expertise in action grounding, temporal consistency, uncertainty, and failure recovery
strong Python and PyTorch/JAX skills in training/adaptation, inference, and experiment design, combined with the ability to inspect C++ and robot-control interfaces
demonstrated own code or model contributions, supported by meaningful baselines and measured hardware outcomes
terminology familiarity or model-API integration alone is insufficient
Personality and Working Practice: you are an architect who writes and debugs code, challenges weak assumptions, and follows ideas through to physical evidence
Enthusiasm: building robot intelligence that combines prediction, reasoning and reliable execution
Languages: very good spoken and written German and English
Additional Information
https://www.bosch-ai.com
www.bosch.com/research
As a global company, we are legally required to comply with applicable EU and U.S. (re-)export control and sanctions regulations. This means that for certain, particularly sensitive positions, we may only hire individuals who have undergone an additional legal screening. This position is one such sensitive role. We will therefore ask you for additional information required for this screening as the application process continues. You can find information about the processing of your data in our Privacy Notice for the application process.
Permanent, open-ended position in the engineering organization for Robert Bosch Robotics GmbH.
Apply with your CV and two concise technical case studies: your contribution, architecture, implementation, evaluation and failure analysis. Include robot results and code, papers or demonstrations where shareable; anonymized technical accounts are accepted.
We offer flexible working models: from part-time options to mobile working and job sharing. Diversity and inclusion are firmly anchored in our culture.
Need support during your application?
Meltem Rudolph (Human Resources)
+49 174 1744961
Need further information about the job?
Jan Schneider-Kraus (Functional Department)
+49 172 9749480
Work #LikeABosch starts here: Apply now!
Summary
Own and implement robotics AI architecture, selecting and adapting world/video-action models, VLA policies, and Code-as-Policy programs, with evaluation across simulation and physical robot rollouts. Requires a Bachelor's or Master's degree, hands-on robotics AI on physical robots, strong Python, PyTorch/JAX, C++ familiarity, and very good German and English.
Responsibilities
Own robotics AI architecture and technical hypotheses; design heterogeneous systems connecting learned models with Code-as-Policy and Graph-as-Policy structures; implement and adapt models and agentic robot programs; define evaluation across simulation and physical rollouts; collaborate with deployment engineer; drive implementation and experiments using the Agentic AI Software Factory
Qualifications
Completed Bachelor's or Master's degree in Robotics, Computer Science, Machine Learning, Control Engineering, or a related field; substantial hands-on robotics AI on physical robots; deep expertise in predictive world/video-action modeling or agentic planning; proven action grounding, temporal consistency, uncertainty, and failure recovery; strong Python/PyTorch/JAX; ability to inspect C++ and robot-control interfaces; demonstrated code/model contributions with baselines and hardware outcomes
Education requirements
Completed Bachelor's or Master's degree in Robotics, Computer Science, Machine Learning, Control Engineering, or a related field
Experience requirements
Substantial hands-on contributions to robotics AI systems on physical robots with defensible architecture decisions and reproducible results; deep expertise in predictive world-/video-action modeling or agentic robot planning and Code-as-Policy; proven expertise in action grounding, temporal consistency, uncertainty, and failure recovery; demonstrated code or model contributions supported by meaningful baselines and measured hardware outcomes
How to apply
Apply with CV and two concise technical case studies covering contribution, architecture, implementation, evaluation, and failure analysis; include robot results and code, papers, or demonstrations where shareable
Benefits
Flexible working models, including part-time options, mobile working, and job sharing