Simulation & Modeling Applied Scientist, Prime Air Flight Sciences High Fidelity Methods

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Come work on the Amazon Prime Air Team!

Prime Air"s Flight Sciences High-Fidelity Methods (HFM) team is seeking an outstanding Applied Scientist to develop and verify drone systems models and flight physics models. These models form the backbone of every flight simulation performed within Prime Air, directly informing aircraft design, system verification, certification, and business decisions.

The HFM team"s work enables prediction of critical vehicle performance metrics-including range, maneuverability, tracking error, and aircraft stability-and connects vehicle design and operational decisions to business outcomes such as customer reachability. Our models are also a crucial input to the design of flight control algorithms and software verification. Because the accuracy and reliability of these models underpin so many facets of Prime Air"s mission, the scientist in this role will have broad, high-visibility impact on the program"s success.

Key job responsibilities

The Applied Scientist in this role will own the end-to-end lifecycle of simulation models-from development and deployment through verification and ongoing maintenance. This begins with gathering downstream customer needs, selecting the most suitable modeling approach and level of fidelity, and coordinating the generation of input data. It extends through model training, development and maintenance of software interfaces, and verification of model accuracy.

A core aspect of this role is determining the right modeling approach for a given physical phenomenon. The scientist will need a working understanding of the physics and systems being modeled, including vehicle aerodynamics, propeller performance, multibody dynamics, atmospheric physics, electric powertrain components, and guidance and navigation system (GNS) sensors. They will design experiments to generate the data needed to build and verify models, and apply uncertainty quantification and statistical analyses to validate model fidelity.