Zipline is looking for a Senior Electromagnetic Engineer to develop and own the analytical and numerical modeling and validation capabilities used to design, select, and optimize electric machines across our aircraft platforms. In this role, you will build a common motor-modeling framework that enables engineers to rapidly explore design spaces, understand performance tradeoffs, and optimize motors as part of the complete aircraft system. You will create and maintain electromagnetic models, performance maps, loss models, and scalable design-space datasets that support motor development from early architecture studies through detailed design and flight validation. You will work closely with mechanical, thermal, power electronics, controls, aerodynamics, systems, and vehicle-performance engineers, evaluating how motor characteristics affect aircraft-level outcomes such as range, payload, acoustic performance, thermal margin, reliability, mass, and cost.

Responsibilities

Develop, validate, and maintain electromagnetic models for Zipline’s propulsion and auxiliary motors.
Build a reusable and well-governed library of motor models, assumptions, material data, winding definitions, simulation results, and validation evidence.
Generate torque-speed envelopes, efficiency maps, loss breakdowns, voltage and current requirements, flux-linkage and inductance maps, demagnetization limits, and fault-performance data.
Create scalable design-space “clouds” and perform sensitivity and uncertainty studies across geometry, materials, windings, temperature, tolerances, and operating conditions.
Develop reduced-order and surrogate models for aircraft optimization, mission simulation, controls development, and thermal analysis.
Integrate motor models with inverter, battery, propeller or driven-load, thermal, and aircraft mission models.
Evaluate motor architectures, electromagnetic materials, supplier concepts, and emerging technologies using first-principles analysis, simulation, and test data.
Optimize designs for efficiency, mass, torque density, thermal performance, acoustic behavior, controllability, reliability, and cost.
Develop model-validation plans that define test objectives, operating points, required measurements, instrumentation accuracy, acceptance criteria, and correlation metrics.
Plan and execute dynamometer experiments to characterize motor performance and validate electromagnetic, loss, and thermal models across relevant operating conditions.
Analyze measurement uncertainty, test repeatability, and sources of discrepancy between simulation and experiment, and use those findings to improve model assumptions and fidelity.
Work closely with test engineers to develop instrumentation and test methods that produce the high-quality data required for model correlation and validation.
Use dynamometer, component, and aircraft test data to calibrate models where appropriate and independently validate their predictive accuracy.

Requirements

Master’s degree or PhD in electrical engineering, mechanical engineering, applied physics, or a related field, with a focus on electric machines, electromagnetics, optimization, or electric powertrains.
Strong understanding of electric-machine fundamentals, including magnetic circuits, winding theory, d-q models, saturation, harmonics, losses, thermal effects, and permanent-magnet behavior.
Significant experience developing and interpreting finite-element and reduced-order models of electric machines.
Experience with Motor-CAD or similar software (JMAG, Maxwell, COMSOL, etc) for electromagnetic, thermal, and performance modeling of electric machines.
Strong proficiency in MATLAB for model development, automation, optimization, data analysis, and visualization.
Experience generating motor maps or reduced-order models for system simulation, controls, or powertrain optimization.
Hands-on experience planning and executing electric-motor dynamometer tests for characterization or model validation.
Experience defining test matrices, selecting appropriate measurements and instrumentation, and interpreting experimental data in the context of model assumptions.
Experience correlating electromagnetic models against dynamometer or hardware test results and diagnosing the root causes of model-to-test discrepancies.
Understanding of experimental uncertainty, repeatability, sensor accuracy, and their impact on model validation
Strong first-principles problem-solving skills and the ability to identify and challenge weak modeling assumptions.
Ability to communicate complex technical results clearly across engineering disciplines.
Demonstrated ownership of technically ambiguous projects from problem definition through recommendation and implementation.

Nice to have

Experience with aerospace, electric aviation, robotics, automotive traction, or other mass- and efficiency-constrained applications.
Experience optimizing multiple motor types across a common vehicle or product platform.
Experience with Motor-CAD (or similar software) python scripting, MATLAB-based optimization workflows, and automated generation of large motor design spaces.
Familiarity with additional electromagnetic tools such as Ansys Maxwell, JMAG, etc.
Knowledge of motor-control techniques, inverter limitations, field weakening, sensorless control, and fault-tolerant operation.
Experience with high-accuracy motor characterization, including efficiency mapping, back-EMF measurement, torque constant, winding resistance, inductance, loss separation, thermal characterization, or cogging torque measurement.
Familiarity with torque transducers, power analyzers, encoders, temperature instrumentation, data-acquisition systems, and other common motor-dyno instrumentation.
Familiarity with thermal-network models, computational fluid dynamics, structural analysis, rotor dynamics, or electromagnetic noise and vibration.
Experience with multi-objective optimization, design of experiments, uncertainty quantification, surrogate modeling, or machine-learning-assisted design exploration.
Experience building internal engineering tools, simulation pipelines, databases, or cloud-based computational workflows.
Familiarity with electrical-steel characterization, permanent-magnet properties, AC winding losses, rotor eddy-current losses, and high-speed machine design.
Experience evaluating emerging motor topologies or technologies and determining whether their system-level benefits justify development risk.
Working knowledge of aircraft performance, propeller or fan loading, battery systems, and mission-level energy optimization.