Head of System Modeling

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 the first instant logistics system that serves all humans equally. Leveraging expertise in robotics and autonomy, Zipline serves tens of millions of people around the world. 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.

The Systems Modeling Team has tremendous power to shape Zipline’s products. We develop physics-based models and use them to architect and optimize our aircraft, as well as the supporting logistics system. Through simulation, we can rapidly explore a vast array of design options for future products, and we can find ways to wring more performance out of our existing products.

Systems Modeling brings diverse teams and fields together (e.g. mechanical, aerodynamics, electromagnetics, electrical, battery chemistry, thermal, controls, fleet operations, economics) to gain new insights. We translate technical conversations into rigorously framed engineering problems. We value asking pertinent questions and generating coherent answers.

You will lead a team of high-caliber engineers applying analytical skills at both the product architectural and fleet operations level. Your team’s contributions will guide and accelerate key decisions during many phases of engineering development, and scaling. Importantly, you will challenge assumptions and requirements – especially those which drive the most cost and complexity. You will relentlessly pursue high-quality insights by improving validation processes, checking simulation results with independent hand calculations, safeguarding model inputs, and calling out where model assumptions are weakly supported by data.

The fundamental role of your team is to build and maintain models that close the loop between product performance goals and hardware/software requirements. For example, this might consist of an aircraft model with subcomponents for motors, inverters, propellers, wings, batteries, position/orientation controllers and more. You’ll zoom in on the finer points of each subsystem:
Should the propulsive motor be mated to a gearbox? How can we design it to supply sufficient torque without overheating, while weighing as little as possible? What type of battery chemistry should be selected, in light of requirements for lifetime, mass, power capability, and energy? You’ll ask critical questions at the system-level:
How much range is an acceptable trade-off for payload mass? How does unfavorable weather impact aircraft performance capabilities? You’ll explore the vast space of mission types, sub-system faults, and other key events to understand their impact on the system.

Your team also optimizes the operational efficiency of the Zipline fleet, directly impacting our customers. What is the smallest number of aircraft that can effectively support a given service area? How might we maximize deliveries per unit hardware by identifying and eliminating bottlenecks, or by adding sophistication to our aircraft dispatching strategy? How should we manage battery charging, given competing objectives of battery life versus charging speed?

Is it best to avoid windier parts of the day, or is it ultimately too costly to sit idle? Your team’s model-driven analysis will link operational decisions with customer-facing outcomes.

• Demonstrated experience building mathematical models and modeling frameworks, across languages, methods, and tools
  • Deep programming experience in Python, MATLAB, or Rust
  • An understanding of numerical methods
  • Strong convictions about the defining attributes of high-quality code tools
• Demonstrated experience integrating simulation tools across platforms and software languages
• A mastery of engineering and physics fundamentals:
  • Energy and power
  • Dynamics (kinematics, forces, moments, acceleration/rotation)
  • Fluids and aerodynamics
  • Heat transfer and thermodynamics
• Experience in fleet-level simulations and optimization
  • Range…