System Modeling Engineer

Zipline•South San Francisco, CA

1d•$145,000 - $185,000

About The Position

Zipline is the world’s largest and most experienced drone delivery service, aiming to serve all humans equally by ensuring access to food, medicine, and essential goods. The company operates the world's largest autonomous logistics system, making deliveries globally. Zipline's system strengthens supply chains, reduces congestion, and provides rapid delivery. The company seeks practical problem solvers who thrive on real-world challenges and rapid growth, motivated by building systems with a direct, meaningful impact. The Systems Modeling Team plays a crucial role in shaping Zipline's products by developing physics-based models to architect and optimize aircraft and the supporting logistics system. Through simulation, the team explores design options and enhances the performance of existing products. They bring together diverse teams and fields to gain insights, translating technical conversations into engineering problems. The team values asking pertinent questions and generating coherent answers. This role will guide and accelerate range and energy modeling during development and scaling phases. The engineer will develop complex simulation capabilities and physics-based models to predict energy consumption across flight phases at various fidelity levels, including highly optimized models for run-time execution. Key areas of focus include powertrain and vehicle modeling (losses, kinematics, thermal, battery/cell performance), and hands-on data analysis through fleet data review and experimental testing. These models will be foundational for energy planning and dynamic routing algorithms. The role also involves challenging assumptions and requirements to drive down cost and complexity, ensuring high-quality insights through improved validation processes, independent hand calculations, safeguarding model inputs, and critically evaluating model assumptions. The team also optimizes operational efficiency, impacting customers directly, by analyzing factors like the minimum number of aircraft for a service area, maximizing deliveries per hardware unit, managing battery charging strategies, and evaluating the trade-offs between avoiding certain operational conditions and idle costs. Model-driven analysis will link operational decisions with customer-facing outcomes.

Requirements

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, Battery and cell chemistry principles, Powertrain modeling: motor electromagnetics, powertrain losses
Fluency in system-level optimization
An ability to distill an open-ended topic into a rigorously framed problem statement
Familiarity with a variety of solution techniques, and the ability to identify an appropriate technique for a given problem
Comfort with empiricism
An ability to interpret complex datasets that span multiple physical realms
Experience designing test campaigns for model validation
Familiarity with practical considerations in embedded algorithm design
Excellent communication skills, particularly in distilling multidimensional solution spaces into straightforward insights
Demonstrated leadership attributes
Awareness of the most critical needs of the company, and motivation to seek out unsolved problems
An ability to drive progress on many projects at once, and to dynamically prioritize projects in a fast-evolving environment
Courage to make tough decisions in the face of imperfect information
Adherence to thorough and well-organized documentation
Patience to teach technical skills to others, while remaining open-minded to learning new skills yourself
Empathy and understanding for the people you work with
5 years related industry experience
BS in Mechanical Engineering, Electrical Engineering, or similar discipline

Nice To Haves

MS strongly preferred

Responsibilities

Develop complex simulation capability and physics-based models for predicting energy consumption per phase of flight, at various levels of fidelity, including highly optimized models that can execute at run-time.
Zoom in on the finer points of powertrain and vehicle modeling, including powertrain losses, vehicle kinematics, and vehicle thermal modeling, and battery/cell performance modeling.
Review large-scale fleet data, or conduct specific experiments to extract physical coefficients.
Challenge assumptions and requirements – especially those which drive the most cost and complexity.
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.
Optimize the operational efficiency of the Zipline fleet, directly impacting customers.
Analyze the smallest number of aircraft that can effectively support a given service area.
Identify and eliminate bottlenecks, or add sophistication to aircraft dispatching strategy to maximize deliveries per unit hardware.
Manage battery charging, given competing objectives of battery life versus charging speed.
Analyze whether it is best to avoid windier parts of the day, or if it is ultimately too costly to sit idle.
Link operational decisions with customer-facing outcomes through model-driven analysis.