Autonomy Droid Perception SWE - Onboard Systems

Skills this role screens for

About the role

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 ML systems behind our autonomy stack must be robust, adaptable, and deeply integrated with the hardware.

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. You’ll build realtime 3D perception ML models that transform multiple camera inputs into scene geometry and semantics that help our mission planner with delivery and package pickup. You’ll develop across the entire perception stack, from optimizing the onboard TensorRT engines to building a data flywheel that finds interesting samples from our long-tail of customer deliveries. You will work closely with the planner team to make sure we build the right system, rather than just the best perception model.

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.

The work

What You'll Do

• Implement, train and evaluate real-time 3D perception models that work with two or more cameras across one or more timesteps
• Deploy and run these models onboard a resource-constrained computer, finding ways to optimize and reduce compute and memory footprints
• Build visualization, introspection and eval tooling to deeply understand model performance both on test datasets as well as “in the wild”
• Work closely with the motion planning team, building an expressive yet compact interface between the two subsystems and tracking the right metrics to ensure we’re always hill-climbing towards a better overall system
• 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 own outcomes for a particular model head or backbone. At the Staff level, you will own roadmapping the future of one or more onboard models and manage cross-functional interfaces in addition to the above.
• Stay up to date with research in the field, drive experimentation, go to conferences and help keep Zipline’s ML modeling stack in lockstep with powerful new paradigms in real-time compute-constrained 3D perception

Also

What You'll Bring

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.

• 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 segmentation, or learned multi-view stereo
• Strong understanding of classical computer vision (e.g. camera calibration, epipolar geometry, structure-from-motion, SGBM stereo) and the ability to blend it with modern ML approaches.
• Expertise and depth with robotics fundamentals: you should be able to reason about reference frames, matrix math, SE(3) manifolds and probabilistic sensor fusion
• Hands-on experience training, iterating on, and optimizing CNN and transformer architectures on target hardware: think NVIDIA Jetson sized compute
• 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.
• At the Senior level, you bring experience with the full ML lifecycle (training, data annotation, evaluation, hard mining)—not just models. At the Staff level, experience influencing design across systems: data pipelines, training infrastructure, compute requirements.
• ML experience on hardware applications is a strong plus - a robot will move based on the outputs of your perception system