Perception Intern (Summer 2026)

Confirmed live in the last 24 hours

Zipline

South San Francisco, California, USA

On-site

Posted March 27, 2026

Job Description

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 Droid Perception Team

This team owns both onboard and offboard (cloud-side) perception systems that inform, validate, and augment our onboard autonomy. From generating rich 3D and semantic priors from aerial survey data to learning customer preferences and terrain features at scale, your work will help define how we prepare Zipline aircraft to perform mission-critical deliveries in complex, real-world environments.

The Role

You'll dive into ML model experimentation, eval and integration - pushing the boundaries of our current perception system. Our distinctive challenges require groundbreaking approaches, and you'll have the chance to see your ideas transition from concept to real-world application. In a fast-paced and collaborative environment, you'll look at current research in the field, and use that to propose novel solutions to our pressing perception challenges. Join us, and be at the frontier of shaping the future of autonomous deliveries.

What You'll Do

Experiment and ideate on learning-based solutions for unique perception challenges.
Transition experimental solutions to scalable, real-world applications.
Collaborate closely with team members, brainstorming and deriving creative solutions from first principles.
Leverage heterogeneous sources of data to train machine learning models
Train models on heterogeneous data sources
Build tools to streamline processes and encourage engineering excellence.
Share findings and insights, fostering knowledge exchange across teams.
Drive the transition of experimental models into practical, operational systems.

What You'll Bring

A proven history of quality ML research, reflected by publications in conferences such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, CoRL, RSS, etc.
Specific expertise in areas such as depth estimation, semantic segmentation, 3D perception, etc.
Proficiency with deep learning frameworks like PyTorch, JAX, or TensorFlow.
Experience writing code in a production environment, e.g. at a previous internship.
Ability to rapidly experiment, iterate, and adapt to new findings in a dynamic environment.

What Else You Should Know

Zipline is unable to sponsor work visas for applicants to this position.

The starting cash range for this internship is $44 - $49 / hour. Please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, an

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