Asks for

The ad says“At least 5+ years of experience (Senior) or 8+ years of experience (Staff) building and deploying deep learning-based perception systems, particularly in 3D geometry, semantic understanding, or mapping from remote sensing data.”
The ad says“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 such as feedforward multi-view models and gaussian splats”
The ad says“Hands-on experience training, fine-tuning, iterating on, and optimizing CNN, transformer and foundation-style model architectures in production environments.”
The ad says“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 such as feedforward multi-view models and gaussian splats”
The ad says“At least 5+ years of experience (Senior) or 8+ years of experience (Staff) building and deploying deep learning-based perception systems, particularly in 3D geometry, semantic understanding, or mapping from remote sensing data.”
The ad says“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 such as feedforward multi-view models and gaussian splats”
The ad says“Experience deploying models in real-world, high-stakes robotics or autonomy applications is a strong plus for Senior and a requirement for Staff.”
The ad says“Train and deploy large-scale models for semantic segmentation, feedforward 4D geometry, and learned preference modeling using aerial survey images, production deliveries and synthetic generated data.”
The ad says“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 such as feedforward multi-view models and gaussian splats”
The ad says“Hands-on experience training, fine-tuning, iterating on, and optimizing CNN, transformer and foundation-style model architectures in production environments.”

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 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. Our operational scale makes this a Physical AI opportunity like no other.

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 onboard, offboard 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 enable Zipline aircraft to scale mission-critical deliveries across complex, real-world environments.

This is not a purely 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 computer vision ML models that run in the cloud (or on our brand new on-prem GPU cluster!), helping us support and scale our on-device perception models.
Train and deploy large-scale models for semantic segmentation, feedforward 4D geometry, and learned preference modeling using aerial survey images, production deliveries and synthetic generated data.
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.
Design evaluation and validation infrastructure to ensure models behave reliably in the field.
Zipline moves fast. On average, every 6 weeks, you will ship a new feature (or sometimes even a new model!) to production.
At the Senior level, you'll lead architectural decisions, drive experimentation, and help the team push the limits of what’s possible with production-grade perception at scale. At the Staff level, you will own roadmapping the future of one or more offboard models in addition to the above.

What You'll Bring

At least 5+ years of experience (Senior) or 8+ years of experience (Staff) 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 such as feedforward multi-view models and gaussian splats
Hands-on experience training, fine-tuning, iterating on, and optimizing CNN, transformer and foundation-style model architectures in production environments.
An engineering mindset focused on outcomes over experimentation—you know how to prioritize what's good enough to ship now and what needs to be architected for scale later.
Familiarity with building training, data annotation, and evaluation pipelines—not just models.
Comfort working across systems: jumping into data pipelines, training infrastructure, or debugging distributed training issues as needed.
Experience deploying models in real-world, high-stakes robotics or autonomy applications is a strong plus for Senior and a requirement for Staff.
At the Staff level, we also expect to see experience bringing up new efforts within your role, and demonstrated examples of building staged roadmaps for challenging ML tasks.

What Else You Need To Know

The starting cash range for this role is $200,000 - $240,000 for Senior and $240,000 - $280,000 for Staff . 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, working location, and projected impact. The total compensation package for this role may also include: equity compensation; overtime pay; discretionary annual or performance bonuses; sales incentives; benefits such as medical, dental and vision insurance; paid time off; and more.

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.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!

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.