Flyzipline
Autonomy Droid Perception SWE - Onboard Systems
South San Francisco, California, USA
Sponsorship not specified$200k-$240kDetected 20 hours ago
Machine LearningDeep LearningData EngineeringNLPComputer VisionA/B TestingRoadmappingLogisticsRoboticsSensorsResearchAdaptability
About the role
- About Zipline Zipline is the world's largest and most experienced drone delivery service.
- 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.
- The drone is only 15% of what we've built to enable seamless, reliable, global operations.
Responsibilities
- 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
- 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
Requirements
- 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.
Nice to have
- ML experience on hardware applications is a strong plus - a robot will move based on the outputs of your perception system
Compensation
- 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.
Benefits
- 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.
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