As a part of the global research, our AI research in Pittsburgh focuses on Multimodal Foundation Models, AI-based Sensing, Driving assistance, agentic AI, and efficient Gen. AI. We develop scalable, intelligent, and trustworthy AI solutions for Bosch products and services in application areas such as advanced manufacturing, smart home and building solutions, advanced driver assistance systems (ADAS), robust AI systems, and AI-based simulators. Originating from Bosch AI research in Pittsburgh, we are responsible for pushing the boundaries of multimodal foundation models and Gen. AI through key innovations to solve complex industry problems, and shape the future of Bosch products and services for both internal and external users. We work with internal partners of different Bosch business units to transfer our solutions into future products. We also actively collaborate with leading groups in academia and industry to promote research ideas and publish research findings in internationally renowned conferences and journals such as ICML, ICLR, ICRA, CVPR, ICCV, ECCV, Neur. IPS, etc.)Conduct research on multimodal foundation models, agentic AI, robustness and efficient Gen. AI to address academic and industrial challenges. Work with an international team of experts to transfer and apply Bosch in-house AI innovations and 3rd-party solutions to Bosch AI products and services, building systems that can advance manufacturing, energy solutions, AI-based sensing, driving assistance, etc. Stay abreast of the latest technological innovations and market trends by attending academic conferences, technical events, and seminars. Offer expert insights to the management team in relevant technology sectors, aiding in strategic planning, R&D trajectory, and investment decisions. Document and disseminate research findings through high-caliber publications and/or patent submissions. Qualifications. Basic Qualifications. PhD. in Computer Science or Engineering, or a related discipline or master’s degree with 3 years industry experience (multimodal foundation model related) after graduation . years of research experience or equivalent graduate research experience on multimodal foundation models, agentic AI, robust and efficient Gen. AI - In-depth experiences in foundation models, with work in at least two of the following areas: time-series data analysis, LL - Ms, VL - Ms/ MML - Ms, inference efficiency, deployment of large models, robustness. Proficiency in one or more programming languages commonly used in systems research (e.g., Python, C ) and hands on experience with AI libraries. Publication record in top venues including ICML, ICLR, ICRA, CVPR, ICCV, ECCV, Neur. IPS, etc. Strong interpersonal, communication, and teamwork capabilities. Preferred Qualifications Strong background in math, statistics, computational modeling 3 years experiences in industrial research. Hands-on experience in product development in the above-mentioned areas for consumer/enterprise markets. Experience in leading R&D project & team dealing with international customers. Leadership skills with excellent English communication & teamwork skills.