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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # System Modeling Engineer - **Company:** Zipline - **Location:** South San Francisco, CA, United States - **Experience:** Expert - **Salary:** $145,000.0 - $185,000.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Algorithm Design, Computer Programming, Python (Programming Language), Kinematics, MATLAB, Systems Integration, Dynamic Routing, Model Validation, Modeling and Simulation - **Published:** August 7, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3343800523&tx=KL1717FFG&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * 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 Minimum Experience: * 5 years related industry experience * BS in Mechanical Engineering, Electrical Engineering, or similar discipline; MS strongly preferred ## Description 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. What You'll Do Your role will guide and accelerate range and energy modeling during development phases and scaling. You will 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. You'll 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. This role is also hands-on with data - whether it's reviewing large-scale fleet data, or conducting specific experiments to extract physical coefficients. These models will form the backbone of our energy planning and dynamic routing algorithms. Importantly, you will challenge assumptions and requirements รข?? 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. 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? 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