Machine Learning Research Perception Intern - Spring 2027 - Santa Clara, CA

Nissan Mexicana, S.A. de C.V. (NMEX)Santa Clara, CaliforniaOn-siteInternshipListed 2 hours ago

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About this role

Location(s): Santa Clara, CA
Job Schedule: 12-week program
Degree Level: Master's - PhD Level Students
Preferred Degree: Computer Science, Electrical Engineering, Robotics, Artificial Intelligence, Machine Learning, or related field

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

We are currently looking for a Machine Learning Research Intern - Perception to join our team in Santa Clara, CA. With a focus on mobility and autonomous driving technologies, Nissan is seeking researchers who want to challenge themselves, develop their skills, and contribute to the future of intelligent vehicles.

On our team, we focus on advancing perception technologies that enable autonomous vehicles to understand and interact safely with their surroundings. Machine learning-based perception models are at the core of modern autonomous driving systems, supporting critical functions such as moving object detection and tracking, road structure estimation, and environmental understanding.

As an intern on the Autonomous Driving Systems team, you will gain hands-on experience validating and evaluating state-of-the-art perception models deployed on autonomous vehicle platforms. Working closely with researchers and engineers, you will evaluate machine learning models using large-scale real-world driving datasets, develop validation methodologies and performance metrics, analyze model behavior under diverse traffic and environmental conditions, and identify opportunities to improve system robustness and reliability.

A Day in the Life:

- Gain hands-on experience evaluating cutting-edge machine learning models for autonomous vehicle perception applications.
- Develop practical skills in perception system validation, statistical performance assessment, data mining, and large-scale dataset analysis.
- Evaluate and benchmark perception models using real-world autonomous vehicle data.
- Analyze model performance under varying environmental, traffic, and operational conditions.
- Develop validation methodologies, performance metrics, and reporting tools to assess system effectiveness.
- Collaborate with experienced autonomous vehicle engineers and researchers on next-generation perception technologies.

Who We’re Looking For:

Required:

- Must be currently enrolled in a Master's or PhD degree program in Computer Science, Electrical Engineering, Robotics, or a related field.
- GPA of 3.0 or above (Candidates will be required to provide an official or unofficial transcript during the application process for verification.)
- Strong programming skills in C++ and/or Python.
- Fundamental understanding of machine learning concepts and methodologies.
- Experience with data analysis and data visualization tools.
- Strong analytical, problem-solving, and communication skills.
- Self-motivated with a willingness to challenge yourself and continuously develop your technical capabilities.
- Ability to work effectively in a collaborative research and development environment.
- Ability to perform work onsite in Santa Clara, CA.

Preferred:

- Experience with computer vision, perception systems, robotics, or autonomous driving technologies.
- Experience with machine learning frameworks such as PyTorch or TensorFlow.
- Familiarity with Linux and Robot Operating System (ROS).
- Knowledge of object detection, object tracking, semantic segmentation, or 3D perception algorithms.
- Experience analyzing large-scale sensor datasets from cameras, LiDAR, radar, or similar sensing systems.

What You’ll Look Forward to at Nissan:

Connection and Collaboration: We offer Business Synergy Teams (ERGs) and opportunities for employees to strengthen relationships and connect with colleagues from diverse backgrounds, fostering a culture of belonging.

Professional Training and Development: Expand your knowledge and skills through Nissan's rich innovation offerings, seminars, learning platforms, and leadership development programs.

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 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