Spatial Planning Intern (Summer 2026)

Zipline•South San Francisco, CA

1d•$40 - $44•Onsite

About The Position

Zipline is on a mission to transform the way goods move. Our aim is to solve the world’s most urgent and complex access challenges by building the first instant logistics system that serves all humans equally. Leveraging expertise in robotics and autonomy, Zipline designs, builds, and operates a fleet of cutting edge, autonomous delivery drones. We serve tens of millions of people around the world. Joining Zipline’s Emerging Talent program as an intern is an opportunity to contribute to our promise of building a system that provides equitable access to critical healthcare supplies for millions of people. We believe that internships are more than just opportunities to learn by watching or doing low level tasks. We expect our interns to take on meaningful work that actively contributes to moving Zipline’s mission forward, while learning real-world skills that will serve them in their careers for the long term. Join us, and build the future of logistics with the best humans around! Zipline builds and operates fleets of delivery drones to get medicine to those who need it, fast, regardless of where they live. To power this, the Spatial Planning Team is building out the long term scalable solutions that enable us to fly in new countries and regions as rapidly as possible. This team is responsible for building tools and services that produce artifacts used by our vehicles to fly their missions in the real world. This means the outputs from the Spatial Planning Team define the places our vehicles will fly in the world, their constraints, and provide strong priors for the real-time system on the vehicle to follow to accomplish its mission safely. In this role you will contribute to, build, and own portions of Zipline’s Spatial Planning stack. That includes contributing to an extensible path planning service used for generating routes that are operationally flown every day. It also includes a suite of services for data generation, transformation and access for path planning and flight data analytics. Your work within the team could range from path planning algorithms, validation of artifacts for compliance with flight requirements, to spatial data generation and data transformation pipelines. Your work will help us achieve multi-objective routing and efficient spatial data ingestion and access, enabling Zipline to serve more customers around the world. From this internship, you can expect to learn about how theoretical path planning algorithms are adapted for a real world problem, and how data and spatial search interact to enable routing in air. Our ideal candidate works well in startup environments, is comfortable wearing many hats, and is excited to learn about many aspects of how Zipline’s spatial planning works today.

Requirements

Must have at least completed the second year of your Undergraduate studies. Masters and PhD students are also eligible.
Proficient coding skills in Python, with an openness to bring new ideas and languages to the table
Ability to write clean, modular code with accompanying documentation
Understanding of automated testing practices and the ability to apply them to produce solid code that can be iterated on quickly
Deep understanding of algorithmic optimization techniques (especially where applied to robotics motion planning)

Nice To Haves

Preferred onsite in South San Francisco
Preferred experience supporting or developing novel algorithmic research
Preferred experience with spatial data

Responsibilities

Work on containerized services that generate spatial planning artifacts
Use GeoData tools to visualize and evaluate land features that impact serviceability
Work with teams to make spatial data accessible instantaneously anywhere in the world
Improve planning algorithms to make routing fast and reliable
Build systems for geoindexing and geo-accessing spatial constraints instantaneously
Adapt current spatial planning to different costs and models and build the infrastructure to enable cost-based search