ABOUT ZIPLINEDo you want to change the world? Zipline uses drones to deliver critical and lifesaving medicine to thousands of hospitals serving millions of people in multiple countries. Our mission is to provide every human on Earth with instant access to vital medical supplies. Join Zipline and help us make this a reality for billions of people.ABOUT YOU AND THE ROLE

Zipline is at the forefront of a logistics revolution, using autonomous aircraft to deliver just-in-time, life-saving medical supplies on multiple continents, 7 days a week. We have completed over 200,000 deliveries; it took over 4 years to reach the first 100,000 deliveries. It took 8 months to reach the last 100,000 deliveries. Do you want to be a part of reaching 1 million life-saving deliveries in the next 2 years? 

We believe access to medical care should not depend on your GPS coordinates. In service of our mission to operate at global scale, we’re growing our perception capabilities, to expand quickly and safely into new products and locations, with the ultimate goal of delivering essential packages right to your doorstep. Our perception team is looking for a software engineer with an expertise in machine learning and artificial intelligence, who is passionate about developing and shipping perception systems for the real world.

WHAT YOU'LL DO

• Design integrated machine learning solutions that enable our highly maneuverable aircraft to perceive general aviation aircraft, power lines, and radio towers and other challenging obstacles, so that we can steer clear of, dodge or otherwise avoid them
• Build software infrastructure to enable learning algorithms to leverage our large-scale fleet data
• Contribute to state-of-the-art machine learning infrastructure and relevant software (e.g. distributed training, continuous model integration, data management, and evaluation of production systems). 
• Address large scale challenges in the machine learning development cycle, especially around distributed training in the cloud and data engineering.
• Stay up to date on the state-of-the-art in deep learning ideas and software
• Implement cutting-edge deep learning models accelerating model training time, improving performance, and tackling open problems
• Understand the inner workings of neural networks to uncover edge cases and make safety determinations
• Design machine learning systems that can understand and communicate when they are not working well.
• Identify and mitigate bottlenecks in our machine learning development processes

WHAT YOU'LL BRING

• Deep understanding of the theory and practice of modern machine learning techniques
• Deep learning expertise: Experience training deep-learning models in an end-to-end fashion, writing custom layers/operations, optimizing networks for inference on embedded systems.
• Clear grasp on basic linear algebra, optimization, statistics, and algorithms.
• Experience working with Pytorch, Tensorflow or other modern deep learning frameworks.
• You are passionate about ML, both large scale engineering and research challenges, especially in the space of autonomous driving and/or robotics.
• Strong software engineering practices in Python with machine learning experience in a production setting.
• Computer vision experience not required, but recommended. 
• Generalist mindset, with the ability to work cross platform, from spooling up cloud compute services to optimizing for embedded systems
• Experience building reproducible data and machine learning pipelines
• Experience deploying machine learning solutions on real robots is a big bonus

WHAT ELSE YOU NEED TO KNOW

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!