Software Systems Validation Intern (Summer 2027)

About Zipline

Zipline is the world's largest and most experienced drone delivery service. We are on a mission to serve all humans equally by ensuring access to food, medicine and essential goods anytime, anywhere. We design, build, and operate the world's largest autonomous logistics system, delivering critical supplies quickly and reliably. Today, Zipline operates on four continents, makes a delivery somewhere in the world every 30 seconds, and has completed millions of deliveries to date, including blood, vaccines, medical supplies, food, and retail products.

Our customers include the world's largest and most prominent healthcare systems, governments, retailers, restaurants and global businesses who rely on us to save lives, reduce emissions, increase economic opportunity, and provide delivery from point A to point B as fast as possible. The drone is only 15% of what we've built to enable seamless, reliable, global operations.

Our system strengthens supply chains, reduces congestion, and gives people time back. With more than 140 million commercial autonomous miles safely flown, Zipline is redefining access to healthcare, consumer products, and food across the globe.

We operate at a global scale and are looking for practical problem solvers who thrive on real-world challenges and rapid growth. Our team is motivated by building systems that have a direct, meaningful impact on people's lives and by scaling the future of logistics. We are seeking people who sculpt from first principles, enjoy facing adversity, and can do the impossible at record breaking speeds.

About the System Validation Team

Zipline's Software Systems Validation team ensures that all the software powering our autonomous delivery aircraft works reliably, safely, and as intended in the real world. We operate at the system level-evaluating how components like navigation, perception, controls, planning, and actuation work together as a cohesive product.

The team partners closely with Embedded Software, Autonomy, Systems Engineering, Test Infrastructure, and Data Platform groups to build validation tools, analyze performance, and identify risks early. Our work spans simulation, hardware testing, data-driven analysis, and system-level evaluations that support deployments across the globe.

As an intern, you'll collaborate with engineers across these domains, gaining hands-on exposure to how industry-leading autonomous systems are designed, tested, and validated at scale.

The Role

As a Software Systems Validation Intern, you will help evaluate the software that enables Zipline's autonomous drone delivery system. You'll contribute to building tests, tools, metrics, and visualizations that help the team understand system performance, identify issues, and ensure reliability before flight.

This role is designed for someone excited to learn how complex robotic systems are validated, who enjoys problem-solving, and who wants to build real-world experience working with autonomy software, data analysis, and systems engineering.

What You'll Do

• Support the design and execution of test scenarios across the autonomous software stack to validate system-level requirements
• Help develop and improve validation tools, workflows, and automation
• Build visualizations or metrics that highlight performance trends, gaps, or regressions
• Work with test infrastructure and data platform teams to run validation pipelines
• Analyze results and contribute to identifying root causes of failures or unexpected behavior
• Document findings and communicate insights to engineering stakeholders

What You'll Bring

• You must have completed the second year of your undergraduate studies in Computer Science, Software Engineering, Aerospace Engineering, Robotics, or a related field. Masters and PhD students are also eligible
• Coursework or project experience in robotics, controls, estimation, navigation, perception, or software development
• Familiarity with testing, debugging, or validation methodologies (academic or project-based experience counts!)
• Experience with data analysis using Python, SQL, or similar
• Basic proficiency with a compiled language such as C/C++ or Rust
• Curiosity, attention to detail, and a desire to learn how autonomous systems are validated in real-world environments

Bonus Skills (Nice to Have)

• Exposure to hardware, actuators, sensors, and interfacing with software
• Experience with robotics competitions, club projects, or research labs
• Interest in requirements development, reliability engineering, or statistical validation

What Else You Should Know

This internship is a full-time position, in-person at our South San Francisco office. We will host our Summer 2027 interns from (May/June - August/September).

The hourly rate for this internship is $54 per hour. Additional benefits may include relocation support, a housing stipend, overtime pay, paid sick time, and other benefits, where applicable and subject to local requirements.

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws or our own sensibilities.

Zipline is also committed to providing reasonable accommodations to individuals with disabilities. Please let your point of contact at Zipline know if you require any accommodations throughout your interview process.

Voluntary Self-Identification

For government reporting purposes, we ask candidates to respond to the below self-identification survey. Completion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring process or thereafter. Any information that you do provide will be recorded and maintained in a confidential file.

As set forth in Zipline 's Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.