About Zipline Do you want to change the world? Zipline is on a mission to transform the way goods move. Our aim is to solve the world’s most urgent and complex access challenges by building, manufacturing and operating the first instant delivery and logistics system that serves all humans equally, wherever they are. From powering Rwanda’s national blood delivery network and Ghana’s COVID-19 vaccine distribution, to providing on-demand home delivery for Walmart, to enabling healthcare providers to bring care directly to U.S. homes, we are transforming the way things move for businesses, governments and consumers. The technology is complex but the idea is simple: a teleportation service that delivers what you need, when you need it. Through our technology that includes robotics and autonomy, we are decarbonizing delivery, decreasing road congestion, and reducing fossil fuel consumption and air pollution, while providing equitable access to billions of people and building a more resilient global supply chain.   Join Zipline and help us to make good on our promise to build an equitable and more resilient global supply chain for billions of people. About You and The Role  

Vision-based perception is a critical capability of Zipline’s Platform 2, required to enable this highly maneuverable aircraft to deliver life saving supplies while staying clear of other aircraft, and dodging obstacles not on any map. 

As a camera integration software engineer at Zipline, you will own the design, development and delivery of a robust embedded camera-based sensing stack, deployed on our GPU-enabled Linux-based flight computers. Your scope begins at the lowest level, with kernel drivers and ISP integration, and goes as high as integration with online and offline perception models, to ensure fast and efficient use of massive amounts of vision data.

We’ve developed initial software integrations for our custom camera modules, and we are searching for an embedded camera software expert to bridge the gap to a robust, reliable, and performant system. In this role, you will work closely with engineers from embedded software, perception, and hardware engineering to ensure each aircraft seamlessly transitions from our manufacturing lines to being a participant in the largest drone delivery network in the world.

What You'll Do   Closely partner with our mechanical, electrical and perception engineers to design and build our custom camera modules and data pipeline - everything from lens selection, to manufacturing test plans, to ISP tuning and compression. Develop Linux kernel drivers to integrate with the NVIDIA Jetson image processing subsystem Own the camera sensor APIs and integration with our in-house Rust-based autonomy execution framework Implement efficient image data management and logging systems that smartly balance between minimizing overhead, latency and power consumption, while preserving reproducibility and development velocity Analyze the runtime characteristics of our camera software in flight to build confidence in its performance, focusing on re-usable, maintainable software and optimizing where required Understand and improve the reliability of the flight software system as a whole, working with hardware and systems engineers to develop comprehensive fault management strategies and hardware-in-the-loop tests Develop metrics, monitoring and troubleshooting capabilities to prepare the system for field deployment at scale What You'll Bring  5+ years of experience building and maintaining real-world deployed embedded systems, and handling the long tail of edge cases to ensure consistently high performance and reliability Strong software engineering skills, with proficiency in at least one strongly typed language. We use Rust, C++ and limited amounts of C, for camera kernel drivers Familiarity with running Linux in resource-constrained environments with real-time requirements; we have an audacious goal of running dense stereo vision algorithms for obstacle detection on our aircraft. Every joule of energy matters and directly relates to our delivery range and max package payload. Experience with embedded camera interfaces (MIPI, GMSL2, etc), the typical integration challenges (including datasheet spelunking!) and ways to overcome them. Experience looking at image-quality problems, tracing them through the software and hardware stack with targeted tests and tools, and root-causing them.  Expertise in HDR imager configurations, and how to tune sensor output for machine learning use cases, as opposed to human perception Curiosity and a willingness to learn and work in a variety of software environments, from kernel module development to build systems and GPU-based autonomy execution frameworks

Our team utilizes a remote, hybrid in-office, and distributed work environment, centered around our headquarters in South San Francisco, CA. 

 

What Else You Need to Know    The starting cash range for this role is $180,000 - $225,000. 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; 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!