Lead Research Scientist-GenAI for 3D Computer Vision

Job Description

As a Lead Research Scientist specializing in Generative AI for 3D Computer Vision, drive innovation at the intersection of GenAI and spatial perception. Lead research and engineering efforts to develop next-generation AI systems for applications in automated driving, industrial automation, and embodied AI. Key responsibilities include:

• Lead research and development in generative AI and 3D computer vision to enable embodied intelligence across domains such as ADAS/AD, robotics, and industrial automation.
• Advance 3D perception capabilities by integrating large-scale vision-language-action models, enhancing reasoning, explainability, and open-world understanding.
• Architect and implement scalable solutions, translating cutting-edge research into robust, real-world systems within Bosch’s platforms.
• Collaborate cross-functionally with global research and engineering teams to ensure seamless technology transfer and system integration.
• Stay at the forefront of innovation by actively engaging with academic and industry communities through conferences, workshops, and technical events.

Contribute to intellectual property through high-impact publications and patent submissions, shaping the future of generative 3D AI technologies.

Qualifications

Basic Qualifications

• Ph.D. in Computer Science with minimum 3 years industry experience after graduation.
• 5+ years of R&D experience, or an equivalent graduate research background, primarily in AI technologies including 3D Computer Vision, Automotive Motion, Behavioral Planning, etc.
• 3+ years of Technical Leadership experience
• Proficiency in one or more programming languages commonly used in machine learning (e.g., Python, C++, Rust) and major machine learning frameworks like PyTorch
• Hands-on experience in computer vision and deep learning, with a strong focus on at least two of the following areas: multimodal transformers or VLMs, multimodal language models, diffusion models, NeRF or gaussian splatting, VLA modeling, 3D scene understanding, sensor calibration, autonomous driving, SfM, behavior modeling / prediction, voxel/BEV grid-based feature representation.
• Strong interpersonal, communication, and teamwork capabilities.

Preferred Qualifications

• Publication record in top venues including CVPR, ICCV, ICRA, ECCV, NeurIPS, ICLR, SIGGRAPH, TVCG.
• Industry experience with building E2E systems and world models for ADAS development.
• Experience in working with hardware systems including sensors such as cameras, depth sensors, IMU, LIDAR, etc.
• Strong background in math and statistics.
• Able to work independently, has strong research and problem-solving skills.
• Good communication and teamwork skills