Technical Lead for End-to-End Autonomous Systems

The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania, and Cambridge, Massachusetts is a part of the global Bosch Group (www.bosch.com), a company with over 70 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence, energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS design. 

As a part of the global research, our AI research in Silicon Valley focuses on Foundation Models, Big Data Visual Analytics, Explainable AI (XAI), Natural Language Processing, Computer Vision & Mixed Reality, Cloud Robotics, Data Science, AI System Engineering, Time-series Analysis. We develop scalable, intelligent, and trustworthy AI solutions for Bosch products and services in application areas such as automated driving (AD), advanced driver assistance systems (ADAS), robotics, smart manufacturing, enterprise AI, health care, smart home and building solutions. 

Originating from the AI research in Silicon Valley, our Intelligent Autonomous Systems group is responsible for enabling future autonomous Bosch products by pushing the boundaries of automated driving, advanced driver assistance systems (ADAS), robotics and automation through key innovations that encompass system architecture and AI components. These include methods for motion planning, high level task planning and decision making as well as systems for making these technologies work on real products by building frameworks that take advantage of technologies in the field of reliable distributed computing. 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 CVPR, ICRA, IROS, RSS, NeurIPS and CoRL.

As a Technical Lead specializing in end-to-end autonomous systems, you drive innovation at the forefront of technology. You will 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 end-to-end trained autonomous systems, spanning from perception to planning, incl. vision-language-action models to enable embodied intelligence across domains such as ADAS/AD, robotics, and industrial automation. 
• Advance perception, planning, reasoning and behavior capabilities by guiding data curation efforts and developing 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 autonomous systems. 

Basic Qualifications 

• Ph.D. in Computer Science with >= 3 years industry experience after graduation. 
• A minimum of 5 years of R&D experience, or an equivalent graduate research background, primarily in AI technologies including Computer Vision, Automotive Motion, Behavioral Planning, etc. 
• A minimum of 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: (modular) end-to-end planners (one-stage or two-stage), multimodal transformers or VLMs, diffusion models, Vision-Language-Action models, world models, sensor calibration, autonomous driving, behavior modeling / prediction. 
• Strong interpersonal, communication, and teamwork capabilities. 
• Industry experience in building (modular) E2E AI systems in ADAS/AD. 

Preferred Qualifications 

• Publication record in top venues including CVPR, ICCV, ICRA, ECCV, NeurIPS, ICLR, SIGGRAPH, TVCG. 
• Experience in real-world deployment and continuous development of autonomous systems, including benchmarking, road testing, closed loop simulation etc. 
• Experience in working with hardware systems including sensors such as cameras, depth sensors, IMU, LIDAR, etc. 
• Strong background in math and statistics. 

Your well-being matters at Bosch! We offer a competitive compensation and a benefits package designed to empower you in every area of your life. This includes premium health coverage, a 401(k) with generous matching, resources for financial planning and goal setting, ample paid time off, parental leave, and comprehensive life and disability protection. We're investing in your success! 

Equal Opportunity Employer, including disability / veterans 

*Bosch adheres to Federal, State, and Local laws regarding drug-testing. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date. 

The U.S. base salary range for this full-time position is $215,000 - $270,000. Within the range, individual pay is determined based on several factors, including, but not limited to, work experience and job knowledge, complexity of the role, job location, etc. Your Recruiter can share more details about the specific salary range for this position during the interview process. 

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