Senior AI Researcher, End-to-End Autonomous Systems

Nissan•Santa Clara, CA

1d•Hybrid

About The Position

Nissan is seeking a Senior AI Researcher to lead research and development of large-scale AI models for autonomous systems. The role focuses on enabling autonomous systems to perceive, reason, predict, plan, and interact with the physical world through unified end-to-end learning frameworks. The researcher will use large-scale real-world driving data collected across global markets and vehicle platforms, and validate research through offline simulation and real-world vehicle testing. The researcher will develop autonomous systems using multimodal data, including camera, radar, map, vehicle-state, and natural-language inputs. The work includes scalable pretraining and fine-tuning strategies for predicting future scene evolution and supporting planning and decision-making across routine scenarios and long-tail edge cases. The role also evaluates emerging techniques from academia and industry and translates them into Nissan’s next-generation autonomy platform. As a member of the Autonomous Systems team, the researcher will shape autonomy-platform architecture and translate research in foundation models for physical-world intelligence into autonomous-driving capabilities. The role includes owning research roadmaps through deployment, contributing to data flywheels and continuous-learning loops, mentoring junior researchers, collaborating across teams, and communicating findings to internal and external audiences.

Requirements

At least a master’s degree in Mechanical, Electrical, or Software Engineering, Computer Science, Applied Mathematics, or a related field.
Either a Ph.D. with at least 3 years of relevant industry, research, or postdoctoral experience, or a master’s degree with at least 5 years of relevant industry or research experience applying large-scale AI models to robotics, autonomous systems, embodied AI, physical-world decision-making, or related fields.
Demonstrated experience building, deploying, and validating AI models on real-time robotic, autonomous, or embedded systems.
Experience using real-world operational data for continuous learning and performance improvement.
Demonstrated expertise in one or more of the following: foundation models for physical-world intelligence; vision-language models; vision-language-action models; world models; generative AI; diffusion models; neural environment modeling; reinforcement learning; self-supervised learning; or large-scale distributed training.
Track record of peer-reviewed publications at leading conferences or journals and of translating research into practical autonomous-driving systems.
Ability to independently formulate research problems, drive technical investigations, and deliver research outcomes from concept through deployment.
Expert-level knowledge of C++, Python, PyTorch, TensorFlow, and TensorRT.

Nice To Haves

Research expertise and in-depth knowledge in intelligent mobility, smart cities, computer science, mathematics or statistics, civil or transportation fields, or a related area.
A solid foundation in software development.
Proficiency in at least one of Python, Java, or C++.
Experience with relational or NoSQL databases, such as PostgreSQL or MongoDB.
Hands-on experience with common machine-learning tools, cloud platforms, and frameworks, such as AWS, TensorFlow, and PyTorch.
A track record of publications and experience filing patents.

Responsibilities

Lead research and development of large-scale AI models for end-to-end autonomous systems.
Develop autonomous systems using multimodal camera, radar, map, vehicle-state, and natural-language data.
Create scalable pretraining and fine-tuning strategies to predict future scene evolution and support planning and decision-making.
Evaluate emerging academic and industry techniques and translate them into Nissan’s next-generation autonomy platform.
Contribute to autonomy data flywheels, including data mining, scenario discovery, model evaluation, and continuous-learning loops.
Own research roadmaps from literature review and research innovation through real-world vehicle deployment.
Use sensors and compute hardware to conduct systematic evaluations and validate models in simulation and real-world vehicle testing.
Deliver reusable research outcomes that support future autonomy-platform work.
Manage evaluations and build trust with office stakeholders and key partners through consistent contributions.
Assist and mentor junior researchers and foster technical excellence and respectful feedback.
Establish cross-functional connections within the Silicon Valley office and across global teams.
Present research findings and roadmaps in internal Tech Talks and to management and executives.
Communicate internal breakthroughs through patents, conference technical reports, and peer-reviewed papers.
Provide bi-weekly updates and participate in sprint planning to drive alignment.