Senior AI Researcher, End-to-End Autonomous Systems

About the role

Location: Silicon Valley Job Schedule: Full-time Hybrid Education Requirement: (List applicable degrees) Sponsorship: No Come Drive Innovation with Us. We are currently looking for a Senior AI Researcher, End-to-End Autonomous Systems to join our team in Silicon Valley.

A Day in the Life: Our people are what drive the business forward and we are looking for researchers who want to challenge themselves, test their skills, develop their talents, and discover their full potential. We're currently looking for a Researcher in End-to-End Autonomous Systems to join our team.

As an AI Researcher, you will lead research and development of large-scale AI models that enable autonomous systems to perceive, reason, predict, plan and interact with the physical world through unified end-to-end learning frameworks. At Nissan, you will have the unique opportunity to develop next-generation autonomy technologies using large-scale real-world driving data collected across global markets and vehicle platforms.

Working at the intersection of frontier AI research and production automotive systems, you will be able to validate new ideas through both offline simulation and real-world vehicle testing.

As a key member of the Autonomous Systems team, you will help shape the future architecture of Nissan's autonomy platform, translating cutting-edge research in foundation models for physical-world intelligence into next-generation autonomous driving capabilities.

Specifically, you will develop autonomous systems using multimodal data including camera, radar, map, vehicle state and natural language with scalable pretraining and fine-tuning strategies, which predict future scene evolution and support planning and decision making across diverse operating conditions, from routine driving scenarios to long-tail edge cases.

You will also evaluate emerging SOTA techniques from academia and industry, translating them into our next-generation autonomy platform.

Required Technical & Execution Skills: Systematic Problem Formulation: Contribute to the design and evolution of large-scale autonomy data flywheels, including data mining, scenario discovery, model evaluation and continuous learning loops, ensuring they are well-positioned within the current academic and industry landscape.

End-to-End Ownership: Take full initiative for research roadmaps, from initial literature review and "SOTA" innovation to final real-world vehicle deployment. Impactful Execution: Deliver complex, high-expertise work on-time, ensuring results are reusable by other researchers and provide an immediate foundation for future autonomy platform.

Experimental Rigor: Formulate research problems with well-thought-out solutions, utilizing latest sensors and compute hardware to perform systematic evaluations. Required Leadership & Collaboration Skills: Stakeholder Management: Manage evaluations and earn trust across the office and with key stakeholders through consistent, high-value contributions.

Mentorship: Actively assist and mentor junior researchers, fostering a culture of technical excellence and respectful feedback. Networking & Autonomy: Operate with high autonomy, establishing strong cross-functional connections within the SV office and broader global teams.

Required Communication & Visibility Skills: Strategic Reporting: Present high-level research findings and roadmaps to internal Tech Talks, management and executives. External Impact: Ability to translate internal breakthroughs into external-facing value through patents, conference tech reports, and peer-reviewed papers. Consistency: Drive alignment through legible, valuable bi-weekly updates and sprint planning.

Who We're Looking for: Required: Education: At least a Master's degree in Mechanical, Electrical, or Software Engineering, Computer Science, Applied Mathematics, or a related field.

Experience: PhD with 3+ years of relevant industry, research, or post-doctoral experience, or Master's degree with 5+ years of relevant industry or research experience in applying large-scale AI models to robotics, autonomous systems, embodied AI, physical-world decision-making problems or related technical fields.

Deployment Experience: Demonstrated experience building, deploying, and validating AI models on real-time robotic, autonomous, or embedded systems, with a track record of continuous learning and performance improvement using real-world operational data.

Expertise: Demonstrated expertise in one or more of the following areas: Foundation Models for physical-world intelligence, including Vision Language Models (VLMs), Vision-Language-Action Models (VLAs), World Models, Generative AI, Diffusion Models, neural environment modeling, reinforcement learning, self-supervised learning, and large-scale distributed training.

Research Impact: Demonstrated track record of peer-reviewed publications at leading conferences or journals and a history of translating research into practical autonomous driving systems. Research Leadership: Demonstrated ability to independently formulate research problems, drive technical investigations, and deliver research outcomes from concept through deployment.

Technical Stack: Expert-level knowledge of C++, Python, PyTorch, TensorFlow, TensorRT.

Desired: Research expertise and in-depth knowledge in technical (e.g. intelligent mobility, smart cities, computer science, math/statistics, civil/transportation, or related) Solid foundation in software development Proficiency in at least one of the programming languages in Python, Java and C++ Experience using relational database or NoSQL database, such as Postgresql, mongodb Hands on experience with the common tools, cloud platforms and frameworks in ML (e.g. Flow, AWS, Tensorflow, PyTorch, etc.)

Track record of publications, experience filing patents What You'll Look Forward to at Nissan: Career Growth and Continuous Learning Opportunities: Benefit from diverse career paths, cross-departmental moves, and innovative learning platforms. Enhance your skills through seminars, leadership training, and tuition reimbursement programs, all while playing a vital role in shaping the future of transportation.

From day one, you'll have the support to tackle challenges and contribute to impactful solutions across our organization. Rewards: Be supported with a Comprehensive Benefits Package, including medical, mental health, parental leave, retirement savings & unique Nissan perks, including discounts on lease vehicles as part of our Employee Lease Program and a Vehicle Purchase Program (VPP).

For more information, access our Nissan Benefits Overview Guide. NISSAN FOR EVERYONE People are our most valuable assets, and Nissan seeks to maximize the power of each individual member of our team. When everyone belongs, the power of NISSAN is undeniable. Nissan aims to improve business results through a workplace and business that meets the needs of our employees and customer base.

Nissan is committed to creating a culture where everyone belongs and employees, customers, and partners feel respected, valued, and heard. We have Business Synergy Teams (BSTs) across the Americas that are open to all employees and seek to connect employees through common interests and foster a company culture where all employees feel supported and included.

Nissan also values inclusion in our business as we respect and recognize the diversity of our customer base and the communities where we do business. We are committed to procuring innovative goods and services, retailing our products, and communicating from a position that will help us continue to offer our customers competitively designed, market-driven products.

Join us as we carry our commitment to our employees and customers into the future. Santa Clara California United States of America Salary Range: $122,001.00 - $256,894.00 Salary Range Estimate: Annual Salary: (Minimum to Maximum of Salary Range noted here). This compensation range represents the minimum and maximum base salary rates at Nissan for jobs assigned to this particular grade level.

Please note that it is uncommon for an employee to be placed at either end of the range. Rather, an employee's actual base salary generally may fall somewhere in between and reflect the employee's unique skills, work experience, education, work location, and market norms. Additionally, pay may be based on comparisons to the base salary rates of other employees with similar backgrounds working in comparable roles.