Embedded Software Engineer (Data Platform), Autonomy

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 the Role Zipline operates the world’s largest autonomous logistics system (ground or air) — and in the coming year, we will be hyper-scaling from thousands to tens of thousands of carefully coordinated drone deliveries in several dense, dynamic U.S. metros. Our Autonomy Motion Planning team is looking for a Senior/Staff Software Engineer who is passionate about developing autonomous systems for the real world. This role will explore cutting-edge approaches to decision making and trajectory planning that will enable more accurate and timely deliveries, putting you in the position to make critical product decisions that will shape our future architectures. What You'll Do Build real-time trajectory generation and decision-making for autonomous flight (search-based, sampling, MPC, convex/non-convex optimization). Design collision avoidance and large-scale multi-agent planning (fleet deconfliction, airspace rules, traffic management) that scales to 10,000+ flights/day. Tackle joint optimization across safety, energy, time, and reliability—balancing mission goals with vehicle/airspace constraints. Plan in uncertain environments with complex dynamics: chance-constraints, robustness to wind/turbulence, degraded sensors, and partial observability. Extend the autonomy stack for new aircraft and payloads; define clean interfaces with perception and controls. Prove it before flight: scenario libraries, SIL/HIL, large-scale sim, log replay, and fault-injection. Mine real fleet data to validate safety metrics (separation, risk, intervention rate), improve models, and burn down long-tail failure modes. Continuously reduce cost/latency (vectorization, warm starts, smart heuristics) while raising reliability. What You'll Bring Master's degree in Computer Science or related field and 3+ years of experience building software for safety-critical systems (aerospace/AV/robotics/medical). Strong in Rust/C++/C for real-time, fault-tolerant code on embedded/Linux. Depth in planning & search (A*/ anytime / RRT*/sampling), trajectory optimization/MPC, or multi-agent deconfliction—shipped on real robots/vehicles. Hands-on with simulation at scale, SIL/HIL, log replay, and metrics-driven validation. Evidence of shipping production-grade autonomy through ambiguous, noisy conditions—owning the last mile to reliability. Systems thinker who collaborates tightly with perception, controls, and flig