2027 Summer Intern, MS/PhD, Systems Engineer, Autonomous Vehicle Networks & Diagnostics
About this role
Designing and building Python infrastructure for real-time diagnostics and health monitoring of vehicle communication networks forms the core daily focus for this internship. The Hardware Systems Architecture team defines foundational electrical, communication, diagnostic, software update, and cybersecurity architecture across multiple autonomous vehicle platforms, sitting at the intersection of hardware and software co-design.
Python infrastructure development, automated verification pipelines, and AI-based developer tooling leverage your skills to rapidly prototype and scale modular software. Partnering directly with Systems Architects, Network Engineers, and Vehicle Security Engineers, you will analyze network data and troubleshoot integration issues across test benches and vehicle fleets. This opportunity suits graduate students aiming to apply their technical knowledge to real-world autonomous vehicle platforms while expanding their skill-set in a collaborative environment.
What you will do
- Design and build Python infrastructure to enable real-time diagnostics and health monitoring for vehicle communication networks across multiple autonomous vehicle platforms.
- Build automated verification and validation pipelines that evaluate vehicle network communication, diagnostic functionality, and system health across test benches and vehicle fleets.
- Create diagnostic checks and monitoring workflows for in-vehicle network security and cryptographic mechanisms while analyzing network performance and timing margins.
- Leverage AI-based developer tooling and AI code generation workflows to rapidly prototype, test, and scale modular diagnostic and verification software.
- Partner with Systems Architects, Network Engineers, and Vehicle Security Engineers to analyze network data, troubleshoot integration issues, and refine multi-platform vehicle requirements.
What you need
- Currently pursuing a Master of Science or Doctor of Philosophy degree in Electrical Engineering, Computer Engineering, Computer Science, Robotics, Mechanical or Automotive Engineering, Systems Engineering, or a related technical field.
- Demonstrate strong proficiency in Python for building modular software infrastructure, automated verification pipelines, and data analysis tools.
- Show high fluency with AI-based tooling and AI code generation, remaining very comfortable and experienced with coding and building end-to-end software projects using modern AI tools.
- Possess a solid foundational understanding of communication networks and protocols, specifically including CAN and CAN-FD.
Nice to have
- Hands-on experience with vehicle or embedded communication networks and diagnostic protocols, as well as Python network tooling like cantools and python-can.
- Basic understanding of cryptography and network security concepts such as message authentication codes, cryptographic authentication, or secure embedded communications.
- Experience building automated test or verification pipelines using pytest and CI/CD or working with hardware-in-the-loop and embedded test benches.
- Hands-on experience in autonomous vehicles, robotics with ROS or ROS2, Formula SAE, EcoCAR, or embedded systems projects.
Benefits
- Generous benefits programs subject to eligibility requirements
Skills and tech stack
Questions candidates ask
What is the remote work policy for this internship?
This will be a hybrid onsite internship position located in Mountain View, CA, USA.
What is the expected compensation for this role?
The expected hourly rate is $70 for Master's students and $85 for PhD candidates.
What communication protocols and tools will I use?
You will work with Python infrastructure to monitor vehicle communication networks including CAN, CAN-FD, and Ethernet, with preferred experience using cantools and python-can.
How does the application and hiring process work?
Resumes are accepted on a rolling basis until the role is filled. To be in consideration for multiple roles, you need to apply to each one individually by targeting your top three choices.