Researcher in Autonomous Vehicle Perception

Location(s): Santa Clara, CA
Job Schedule: Full-time – onsite
Degree Level: Master’s Degree

Sponsorship: No

Shape the Future of Mobility at Nissan: Launch Your Career, Drive Innovation

We’re currently looking for a Researcher in Autonomous Vehicle Perception to join our team in Santa Clara, CA. As Perception Researcher, you will work with appropriate training datasets, select and train advanced networks for road user detection and/or road structure estimation, and will evaluate your work both offline in simulation and online in real-world testing. As a member of the Autonomous Systems team, you will get to research and develop perception algorithms that scale from simple scenes to complex intersections thereby ensuring predictable, safe, and human-like autonomous vehicle behavior.

A Day in the Life:   

• Systematic Problem Formulation: Lead the architectural design of perception and road structure estimation algorithms, 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 stacks.
• Experimental Rigor: Formulate research problems with well-thought-out solutions, utilizing latest sensors and compute hardware to perform systematic evaluations.
• 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: Master’s in CS, EE, ME, Applied Mathematics, or a related field required. PhD in similar filed is preferred.
• Experience: Minimum of 3 years of professional hands on exp or pfieldoc research experience in autonomous vehicles required.
• Machine Learning: Strong understanding of BEV encoders, LSS transforms, Sparse Instance-based Modeling, Spatial-Temporal Transformers, Deformable Attention, and/or Reasoning Backbones.
• Technical Stack: Expert-level knowledge of C++, Python, PyTorch, TensorFlow, TensorRT.

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 is committed to a drug-free workplace. All employment is contingent upon the successful completion of drug and background screenings in accordance with Nissan policies and in compliance with federal, state, and local laws, including the California Fair Chance Act and the Los Angeles County Fair Chance Ordinance. Nissan will consider qualified candidates with arrest or conviction records for employment in a manner consistent with these laws.

It is Nissan’s policy to provide Equal Employment Opportunity (EEO) to all persons regardless of race, gender, military status, disability, or any other status protected by law. Candidates for this position must be legally authorized to work in the United States and will be required to provide proof of employment eligibility at the time of hire; Nissan uses E-Verify to validate employment eligibility.

NISSAN FOR EVERYONE

People are our most valuable assets, and diversity and inclusion are the key to maximizing the power of each individual member of our team.  When everyone belongs, the power of NISSAN is undeniable.  Our Corporate Diversity Initiative aims to improve business results by ensuring that our workplace and core businesses meet the unique 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 over 10 Business Synergy Teams (BSTs) across the U.S. and Canada that connect employees – with shared characteristics or interests – build allies, and foster a company culture where all employees feel supported and included.

Nissan also values inclusion in all areas of our business as we strive to mirror 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 diverse perspective which will help us continue to offer our customers competitively designed, market-driven products.

Join us as we carry our commitment to diversity and inclusion into the future.

Santa Clara California United States of America

Salary Range:

$96,776.00 - $198,752.00

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.