Research Scientist - Cyber-Physical AI & Reasoning

** Company Description*
* ** We Are Bosch.*
* At Bosch, we shape the future by inventing high-quality technologies and services that spark

enthusiasm and enrich people's lives. Our areas of activity are every bit as diverse as our outstanding

Bosch teams around the world. Their creativity is the key to innovation through connected living,

mobility, or industry.

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The Bosch Research and Technology Center North America - with offices in Pittsburgh, Pennsylvania, Sunnyvale, California, and Watertown, Massachusetts - is part of the global Bosch Group (  ), a company with over 70 billion euro revenue, 400,000 people worldwide, a very diverse product portfolio, and a history of over 125 years. The Research and Technology Center North America (RTC-NA) is committed to providing technologies and system solutions for various Bosch business fields primarily in the areas of Robotics, Human Machine Interaction (HMI), Energy Technologies, Internet Technologies, Circuit Design, Semiconductors and Wireless, and MEMS Advanced Design.

** Job Description*
* ** Cyber-Physical AI and Reasoning (Engineer / Researcher)*
* The  
** Cyber-Physical AI and Reasoning
** group at  
** Bosch Research Pittsburgh
** develops intelligent systems that tightly integrate  
** learning, reasoning, perception, and physical interaction** . Our mission is to build  
** safe, robust, and adaptive cyber-physical systems
** that operate reliably in real-world environments-spanning robotics, automation, manufacturing, and intelligent devices.

We focus on systems that combine  
** data-driven learning with structured models, physical constraints, and embedded intelligence** , enabling machines to sense, decide, and act across diverse scenarios while continuously improving over time, including through interaction with humans.

** Core Research & Development Areas*
* Our work spans a broad range of  
** Cyber-Physical AI
** topics, including but not limited to:

+  
** Embodied and Cyber-Physical AI*
* + Robot learning and control in physical environments

+ Dexterous manipulation and automation for manufacturing

+ Human-machine interaction and shared autonomy

+  
** Hybrid and Model-Based AI*
* + Combining learning-based models with physics-based, symbolic, or optimization-based components

+ World models, state estimation, and system identification

+ Safety-aware and constraint-driven learning and control

+  
** Multimodal & Foundation Models*
* + Vision-Language(-Action) models for perception, planning, and control

+ Representation learning across modalities (vision, language, proprioception, signals)

+ Cross-domain and cross-embodiment generalization

+  
** Cyber-Physical Systems & Embedded Intelligence*
* + Embedded ML and edge AI for real-time systems

+ Integration of learning algorithms with sensors, actuators, and control stacks

+ Sim-to-real transfer and deployment on physical platforms

+  
** Engineering & Prototyping*
* + System prototyping

+ Data collection pipelines, simulation environments, and benchmarking frameworks

+ Deployment of AI systems to industrial settings

** Role & Responsibilities*
* Depending on background and seniority, candidates will contribute to a mix of  
** research and engineering activities** , including:

+ Defining and investigating compelling problems in  
** Cyber-Physical AI & Reasoning*
* + Designing, implementing, and evaluating learning-based or hybrid AI systems

+ Conducting literature reviews and translating insights into practical system designs

+ Developing experimental pipelines (simulation, real-world testing, data collection)

+ Analyzing system performance, robustness, safety, and failure modes

+ Collaborating with interdisciplinary teams spanning AI, robotics, and engineering

+ Contributing to:

+ Research publications and technical reports

+ Industrial patents and…