Systems Modeling and Optimization Engineer

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. Using 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 the Systems Modeling Team

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, 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. 

The Role

You will apply analytical skills at both the product architectural level and the fleet operations level. Your contributions will guide and accelerate key decisions during many phases of engineering development. 

Fundamentally, you will build and maintain models that close the loop between aircraft performance goals and hardware 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, subsystem faults, and other key events to understand their impact on the system.

You’ll also optimize the operational efficiency of the fleet, directly impacting our customers. What is the smallest number of aircraft that can effectively support a given service area? How might we maximize throughput of a shipper site by intelligently scheduling pre-planned orders? 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 model-driven analysis will link operational decisions with customer-facing outcomes. 

What You'll Bring 

• A track record of problem-solving and product improvement through model-based analysis. You know how to pose the right questions that get to the core of the challenge at hand.
• A strong understanding of fundamental physics:
  • Energy and power
  • Heat transfer and thermodynamics
  • Electrical circuits
  • Fluids and aerodynamics
  • Dynamics (kinematics, forces, moments)

• Demonstrated modeling experience across languages, methods, and tools. Bring your deep understanding of the universal aspects of building and utilizing system models.
• Experience using at least one of the following: Python, Julia or MATLAB.
• A basic understanding of numerical methods and optimization fundamentals — with the curiosity and drive to learn more.
• Knowledge of basic control systems, e.g. thermal, electrical or mechanical.
• Experience interacting with complex datasets that span multiple physical realms.
• Experience designing test campaigns for empirical model validation.
• Excellent communication skills, especially when it comes to explaining a complex system in simple terms.