Do you want beneficial technologies being shaped by your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.
We are seeking an accomplished and visionary AI Engineer to drive the transformation of our manufacturing systems through cutting-edge artificial intelligence technologies. This role requires deep technical expertise in Computer Vision and Deep Learning, coupled with capabilities in Agentic AI, to translate AI technology into measurable business value.
As a core member of our digital transformation initiative, working closely with product managers, solution architects, full-stack developers, and data engineers, you will design and deliver AI solutions.
- Requirement Analysis: Collaborate with business stakeholders and plant teams to understand use-case requirements and pain points, translating them into robust technical specifications.
- CV & Deep Learning Development: Design, train, and deploy classical vision algorithms and deep learning models for industrial inspection and automation, balancing accuracy, robustness, and real-time performance.
- Agentic AI Solutions: Develop and implement Agentic AI workflows leveraging Large Language Models (LLMs) to solve manufacturing problems, such as intelligent document processing, automated reporting, and complex decision support.
- Time-series & Multimodal Data: Process and analyze time-series sensor data alongside visual data to build comprehensive AI solutions for predictive maintenance and process optimization, supporting broader factory AI initiatives.
- Deployment & Integration: Partner with engineering teams to deploy AI models from PoC to production environments, including edge computing integration on the manufacturing line.
This position is ideal for individuals who are passionate about industrial innovation, capable of bridging the gap between research and operations, and ready to shape the future of intelligent manufacturing.
Skills
- CV & Deep Learning: Proficient in computer vision and deep learning algorithms (e.g., object detection, semantic/instance segmentation, anomaly detection); familiar with modern architectures and frameworks.
- Agentic AI: Solid understanding of Large Language Models (LLMs) and Agentic AI frameworks (e.g., LangChain, LlamaIndex); experience in building LLM-driven agents for task planning and tool usage is a strong plus.
- Data & Math: Familiarity with time-series data processing and feature engineering. Solid foundation in statistics, linear algebra, and numerical optimization.
- Programming & Engineering: Proficient programming skills with good engineering practices; fluent in Python (preferred) or C++; experience with model optimization and edge deployment is a plus.
- Communication: Strong ability to articulate complex technical concepts to diverse audiences. Excellent communication skills to explain AI topics to non-technical stakeholders; working proficiency in English (spoken and written).
Experience
- Hands-on experience developing proof-of-concept (PoC) or prototype AI models (internship or academic research projects count).
- Proven experience in Computer Vision projects; experience with LLM-based Agent applications is highly desirable.
- Experience in applied AI or advanced analytics within industrial or manufacturing-related scenarios is a significant plus.
- Experience participating in AI solution design or feasibility studies, from problem definition to conceptual solution architecture is a plus.
- Experience working with cross-functional teams (e.g., product, IT, OT, data teams) to translate business problems into AI-driven approaches is a plus.
Education
- Master’s degree in Computer Science, Artificial Intelligence, Computer Science, Applied Mathematics, Statistics, or a related field (fresh graduates are welcome); OR Bachelor’s degree in the above fields with 2+ years of relevant working experience. Strong ability to read and analyze technical and research literature.
- Formal training or coursework related to deep learning, decision systems, or industrial informatics is a plus.