Senior Aerodynamic Engineer positions focus on delivering results in their domain. This page aggregates open Senior Aerodynamic Engineer roles and what employers typically expect.
Turning Space into a Transportation Layer for Earth Who We Are: Inversion builds advanced reentry systems to deliver next-generation capabilities from space. Our mission is to make Earth radically more accessible by turning Low-Earth Orbit into an on-demand logistics domain. We see space not as a destination, but as a platform — one that unlocks unprecedented speed and global reach. Our spacecraft are designed to deliver payloads anywhere on Earth in under an hour, operating through extreme reentry conditions and landing with high precision. These systems open the door to new ways of testing, delivering, and operating at hypersonic speeds. Inherently dual-use, our technology is built to meet urgent national security needs while laying the groundwork for future commercial applications. Backed by leading investors including Y Combinator, Spark Capital, and Lockheed Martin Ventures, and working with partners such as the U.S. Space Force and NASA, Inversion is pushing the boundaries of what's possible in space-based defense and logistics. What You'll Do: Inversion's reentry vehicles fly from orbital velocity to a precision landing, and every design decision, simulation, etc. along the way rests on an accurate characterization of how the vehicle flies. As a Senior Aerodynamics Engineer, you will generate and database the aerodynamic characteristics of our vehicles across the full flight envelope, aggregating data from high-fidelity CFD, lower-order methods, and wind tunnel testing into database products that drive system-level simulations. In this role, you will: Develop and maintain aerodynamic force and moment databases spanning the full flight envelope, from hypersonic entry through terminal flight Predict the aerodynamic forces and moments acting on Inversion reentry vehicles using high fidelity CFD tools across their flight envelopes. Apply lower-order tools — panel codes, Newtonian aerodynamics, and handbook methods — to efficiently populate the broader envelope Aggregate data of varying fidelity into coherent database products and define associated uncertainties to drive 3-DOF and 6-DOF system-level simulations Support downstream users across GNC, simulation, and mission design in applying the databases correctly Build and mature the tooling and automation behind database generation and delivery Refine models using wind tunnel and flight-testing data Required Qualifications: Bachelor's degree in Aerospace or Mechanical Engineering, or equivalent experience Typically, 5+ years of experience in aerodynamic analysis of aerospace vehicles (reentry, hypersonic, missile, launch, or high-performance aircraft systems) Experience with high-fidelity CFD analysis of compressible external flows (e.g., FUN3D, OVERFLOW, CART3D, US3D, Kestrel, or similar) Experience with lower-order aerodynamic prediction methods, such as panel codes and Newtonian/modified Newtonian aerodynamics Experience with handbook methods and empirical aerodynamic correlations Experience aggregating aerodynamic data from sources of varying fidelity into an overall database product used to drive vehicle simulation and design Strong fundamentals in compressible aerodynamics across speed regimes and in vehicle static and dynamic stability Proficiency in programming languages like Python, MATLAB, C++, or Fortran for analysis tooling and automation Proven ability to work effectively in a fast-paced environment, including prototyping and rapid iteration of new products This position is on-site at Inversion HQ in Playa Vista, CA. Must have the ability to obtain and maintain a U.S. government Secret/Top Secret security clearance. Desired Qualifications: Master's or PhD in Aerospace or Mechanical Engineering, or an equivalent field Experience with the aerodynamics of reentry, hypersonic, or lifting-body vehicles Experience with uncertainty quantification and the definition of aerodynamic dispersions for Monte Carlo simulation Experience reconciling aerodynamic models against…