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3D Perception Engineer - Autonomy; Droid

Job in South San Francisco, San Mateo County, California, 94083, USA
Listing for: Zipline
Full Time position
Listed on 2026-04-17
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Robotics, Software Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: 3D Perception Engineer - Autonomy (Droid)

About Zipline

Zipline is the world’s largest and most experienced autonomous delivery service, founded to serve all humans equally by ensuring access to 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 including blood, vaccines, medical supplies, food, and commercial products.

Our customers include healthcare systems, governments, retailers, and global brands who rely on us to save lives, reduce emissions, increase economic opportunity, and provide new logistics services at scale.

Our technology goes beyond drones. We deploy integrated logistics infrastructure that strengthens supply chains, reduces congestion, and enables instant delivery, transforming how essential goods reach people everywhere. 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.

About You and The Role

Zipline is operating the world’s largest autonomous logistics network—delivering critical medical and commercial goods globally with high reliability, precision, and scale. As we expand into increasingly complex, safety‑critical environments, the systems behind our autonomy stack must be robust, adaptable, and deeply integrated—especially at the intersection of perception and deployment.

We’re hiring senior and staff perception engineers to join our Droid team, the group responsible for the autonomy that powers Zipline’s backyard delivery experience. This team owns the full stack of off‑board and 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 define how we prepare Zipline aircraft to perform mission‑critical deliveries in complex, real‑world environments.

This is not a research role—you’ll be expected to move fast, ship production‑grade systems, and find clever ways to apply state‑of‑the‑art techniques to tangible, high‑impact problems.

What You’ll Do
  • Own the design and implementation of cloud‑side autonomy pipelines that directly support and scale our onboard perception stack.
  • Leverage satellite imagery, aerial surveys, and structured data to build semantic and geometric world models of customer delivery zones.
  • Design and ship tools that predict deliverability, generate high‑fidelity priors, and reduce the operational friction of onboarding new customers in new environments. You’ll step in where our on‑vehicle capabilities can’t solve the problems we need to solve in order to scale the product.
  • Train and deploy mid‑ to large‑scale models for semantic segmentation, 3D geometry, and learned preference modeling.
  • Design evaluation and validation infrastructure to ensure models behave reliably in the field.
  • Work across engineering to integrate your work into fleet‑facing autonomy systems.
  • Lead architectural decisions, drive experimentation, and help the team push the limits of what’s possible with production‑grade perception at scale.
What You’ll Bring
  • At least 5+ years of experience building and deploying deep learning‑based perception systems, particularly in 3D geometry, semantic understanding, or mapping from remote sensing data.
  • Strong understanding of classical computer vision (e.g. camera calibration, epipolar geometry, structure‑from‑motion) and the ability to blend it with modern ML approaches.
  • Hands‑on experience training, iterating on, and optimizing CNN and transformer architectures in production environments.
  • An engineering mindset focused on outcomes over experimentation—you know how to prioritize what’s good enough to ship now…
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