Autonomy AI Systems Integration Intern

InternHunt; Palo Alto, Northern (CA, KY); Hybrid; USD 18,000 - 24,000; Full time

Benefits offered by this job

Medical plans

Dental and vision

401(k)

Paid holidays

Volunteer benefits

Job summary

Tesla’s Autonomy team seeks an Integration Engineer Intern to work on AI platforms and robotics software across vehicle and humanoid platforms. You will contribute to the Autopilot stack, write robust C/C++ and Python code, and collaborate with hardware, AI, and controls teams to push autonomous capabilities forward.

The role emphasizes software in real-time embedded environments, cross-platform integration, and hands-on work with simulation, validation, and fleet data analysis.

Qualifications

• Pursuing a degree in CS, Physics, Computer Engineering with graduation May 2027–May 2028.
• Experience in C/C++ (C++14/17/20), multithreading, and Python; CUDA/OpenCL a plus.
• Strong embedded systems understanding and real-time software design principles.
• Knowledge of computer vision / ML and their real-world applications is a plus.
• Experience with CAN, Ethernet, TCP/IP in automotive contexts.
• Proficient in Linux-based development; embedded Linux and cross-compilation a plus.

Responsibilities

• Write, debug, and maintain robust C/C++ software for Autopilot and humanoid robot stacks.
• Integrate Autopilot features with interfaces and vehicle systems.
• Develop features through simulation, validation, and fleet data analysis.
• Optimize features to minimize power consumption.
• Bring up Autonomy features on new vehicle and compute platforms.

Skills

C/C++

Multithreading

Python

Linux

Embedded systems

CAN/Ethernet/TCPIP

Education

Pursuing CS/Physics/CE degree

Tools

CUDA

OpenCL

Job description

Tesla’s Autonomy team seeks an Integration Engineer Intern to work on AI platforms and robotics software across vehicle and humanoid platforms. You will contribute to the Autopilot stack, write robust C/C++ and Python code, and collaborate with hardware, AI, and controls teams to push autonomous capabilities forward.

The role emphasizes software in real-time embedded environments, cross-platform integration, and hands-on work with simulation, validation, and fleet data analysis.