Autonomous Driving Planning & Control Intern - Hands-on

Roboticsconnected; Santa Clara (CA); On-site; USD 42,000 - 54,000; Full time

Job summary

NVIDIA is seeking a Planning and Control Adaptation Intern for its autonomous driving team in Santa Clara, CA. You will work with experienced engineers to support integration and adaptation across multiple vehicle platforms while gaining hands‑on experience in issue analysis, algorithm validation, and engineering tool development.

You will collaborate on parameter tuning, validation, and tooling using Python or C++ and ROS, CARLA, and related platforms.

Qualifications

• Pursuing a Master’s or PhD in CS, Robotics, Automotive Eng or related field.
• Strong C++ or Python skills; familiarity with Linux development and debugging workflows.
• Foundational knowledge of motion planning, vehicle control, or numerical optimization; strong analytical and teamwork skills.
• Excellent English communication; able to collaborate with global teams.
• Available to work at least three days per week during the internship.

Responsibilities

• Assist planning and control integration, parameter tuning, and adaptation across vehicle platforms.
• Analyze path and speed planning, lane changes, merging, intersections, and lateral/longitudinal control.
• Use simulation, replay tools, and vehicle logs to reproduce issues, investigate root causes, and validate improvements.
• Perform cross-carline testing and evaluate safety, comfort, smoothness, and robustness.
• Develop Python or C++ tools for log analysis, parameter comparison, regression testing, and visualization.
• Collaborate with Planning and Control engineers on integration, validation, and delivery for production autonomous driving programs.

Skills

C++

Python

Linux

Analytical

Teamwork

Education

Master's or PhD in CS/Robotics/Automotive Eng

Tools

ROS

CARLA

Apollo

Autoware

CarMaker

Job description

NVIDIA is seeking a Planning and Control Adaptation Intern for its autonomous driving team in Santa Clara, CA. You will work with experienced engineers to support integration and adaptation across multiple vehicle platforms while gaining hands‑on experience in issue analysis, algorithm validation, and engineering tool development.

You will collaborate on parameter tuning, validation, and tooling using Python or C++ and ROS, CARLA, and related platforms.