- Страна
- США
- Зарплата
- 180 000 $ – 265 000 $
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Senior or Staff MLE - Droid Perception (Offboard)
Zipline — лидер индустрии с благородной миссией и уникальными техническими вызовами. Высокая заработная плата, работа с реальным "железом" и возможность влиять на архитектуру глобальной логистической сети делают эту вакансию крайне привлекательной.
Сложность вакансии
Роль требует глубоких знаний как в современном ML (трансформеры, сегментация), так и в классическом компьютерном зрении (эпиполярная геометрия, SfM). Высокая планка ответственности за системы, работающие в реальном мире и влияющие на безопасность полетов.
Анализ зарплаты
Предлагаемый диапазон ($180k - $265k) полностью соответствует и даже немного превышает рыночные стандарты для Senior/Staff MLE в Кремниевой долине, где медиана составляет около $210k-230k без учета опционов.
Сопроводительное письмо
I am writing to express my strong interest in the Senior/Staff MLE position for the Droid Perception team at Zipline. With over five years of experience in developing production-grade deep learning systems, I have a proven track record of blending classical computer vision with modern transformer architectures to solve complex 3D geometry and semantic segmentation challenges. My background in processing remote sensing data and building robust evaluation pipelines aligns perfectly with Zipline's mission to create high-fidelity world models for autonomous delivery.
What excites me most about Zipline is the focus on 'sculpting from first principles' and the direct real-world impact of your technology. I am particularly drawn to the challenge of building offboard perception systems that generate semantic priors from aerial surveys, as I believe this is the key to scaling autonomous operations in diverse environments. I am eager to bring my engineering-first mindset to your team to help ship reliable, mission-critical autonomy systems that serve people globally.
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Присоединяйтесь к Zipline, чтобы создавать системы компьютерного зрения, которые спасают жизни и меняют будущее логистики по всему миру!
Описание вакансии
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.
We're hiring senior and staff perception engineer 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 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 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 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.
Why This Team?
- You’ll own real-world autonomy problems that matter—delivering essential goods around the world, in thousands of diverse backyards and environments.
- You’ll have autonomy and trust to define the roadmap and drive architectural decisions that shape Zipline’s global operations.
- You’ll work on cutting-edge problems with people who care deeply about quality, systems thinking, and solving hard problems with elegance and clarity.
A Few More Things
Zipline is an equal opportunity employer and encourages candidates from historically underrepresented backgrounds to apply—even if you're not sure you're a perfect fit. If you care about shipping high-impact autonomy systems in production, we want to hear from you.
What Else You Need to Know
The starting cash range for this role is $180,000 - $265,000. 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, ancestry, national origin, religion or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other characteristics protected by state, federal or local law or our other policies.
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!
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- Python
- Computer Vision
- Deep Learning
- CNN
- Transformers
- 3D Geometry
- Semantic Segmentation
- Structure from Motion
- Camera Calibration
- Remote Sensing
- Distributed Training
Возможные вопросы на собеседовании
Проверка фундаментальных знаний в области компьютерного зрения, необходимых для работы с картами и 3D-сценами.
Можете ли вы объяснить принципы работы Structure-from-Motion (SfM) и как вы бы интегрировали эти данные в современную ML-модель восприятия?
Вакансия подчеркивает важность создания систем, готовых к эксплуатации, а не просто исследований.
Расскажите о случае, когда вам пришлось пожертвовать сложностью модели ради производительности или надежности в продакшене. Как вы принимали это решение?
Работа включает использование спутниковых снимков и данных аэрофотосъемки.
С какими специфическими проблемами вы сталкивались при работе с данными дистанционного зондирования (например, изменение освещения, надирные vs косые снимки) и как их решали?
Для масштабирования Zipline нужны надежные пайплайны данных.
Как бы вы спроектировали систему автоматической разметки и валидации данных для обучения моделей семантической сегментации в новых регионах присутствия?
Оценка навыков системного проектирования в контексте робототехники.
Как эффективно распределить задачи восприятия между бортовым компьютером дрона (onboard) и облачной инфраструктурой (offboard) для минимизации рисков при доставке?
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- Страна
- США
- Зарплата
- 180 000 $ – 265 000 $