Aircraft Software Integration Intern (Spring 2027)

Zipline•South San Francisco, CA

5d•Onsite

About The Position

Zipline is the world’s largest and most experienced drone delivery service, aiming to serve all humans equally by ensuring access to essential goods. They operate the world’s largest autonomous logistics system, making deliveries globally. The Software Integration team is crucial for ensuring the reliability and safety of the software that flies their aircraft. This internship offers hands-on experience at the intersection of robotics, embedded software, and systems engineering, focusing on integrating and testing features that impact aircraft flight, route adaptation, and response to unexpected situations. Interns will work with simulation tools, flight telemetry, and testing infrastructure to ensure software behaves correctly before deployment. This is an opportunity to learn about building and scaling large, safety-critical autonomy systems and contribute to technology with a direct community impact.

Requirements

Currently pursuing a Bachelor’s or Master’s degree in Mechanical Engineering, Mechatronics, Robotics, Electrical Engineering, Computer Science, or a related technical field.
Familiarity with Python for scientific programming (libraries such as NumPy, Pandas, SciPy, Plotly, etc.).
Basic understanding of SQL for querying and working with data.
Coursework or experience with statistics, linear algebra, or numerical methods.
Interest in applying engineering and data analysis to solve real-world problems.
Curiosity and analytical thinking to approach technical challenges.
Ability to learn how to frame engineering problems as data science problems.
Willingness to communicate findings clearly with technical and non-technical teammates.
Strong written and verbal skills for documentation and presentations.

Nice To Haves

Exposure to software development practices (version control with Git, debugging, documentation) is a plus.
Familiarity with machine learning concepts or frameworks (e.g., Scikit-learn, TensorFlow, Keras).
Some experience from coursework, projects, or self-study in building or experimenting with models.
Prior exposure to robotics systems, automation, or sensor data (through coursework, projects, or clubs) is a plus.
Exposure to object-oriented programming (e.g., C++ or Java) is a bonus.
Familiarity with cloud services (AWS, GCP, Azure) or big data tools (Spark, Hadoop) is helpful but not required.

Responsibilities

Assist in analyzing datasets from engineering systems, vehicle sensors, and other sources to uncover patterns and support predictive modeling efforts.
Help design clear and visually appealing charts and dashboards using tools such as Matplotlib, Seaborn, Plotly, or Tableau to communicate findings.
Contribute to the creation and maintenance of real-time dashboards that track key metrics and system performance.
Support data cleaning, preprocessing, and organization tasks to make datasets ready for analysis. Write simple SQL queries and learn how to work with databases.
Gain exposure to machine learning by assisting with model development and validation for autonomy applications.
Learn to apply scientific and engineering programming techniques to develop small data pipelines, automate processes, and run simulations.
Support software-related tasks such as building scripts or tools to improve workflows and automation.