Senior Aerodynamics Engineer

Inversionspace · Playa Vista, California, United States · Engineering

Posted 2026-10-18

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Position Overview:

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

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 flight test data, including aerodynamic parameter identification

Familiarity with Fidelity Pointwise, Link3D, or equivalent meshing software for generating high-quality meshes

Experience with high-performance computing environments and large-scale CFD campaign automation

Experience with wind tunnel testing, including test planning, execution, and/or data reduction

Familiarity with 6-DOF flight simulation as a downstream consumer of aerodynamic databases

Prior experience working in startups and/or small independent teams

Our office headquarters is located in Playa Vista, CA. This position requires in-office presence.

The California annual base salary for this role is currently $137,000-$193,000.  Pay Grades are determined by role, level, location, and alignment with market data.  Individual pay will be determined on a case-by-case basis and may vary based on the following considerations: interviews and an assessment of several factors that are unique to each candidate, job-related skills, relevant education and experience, certifications, abilities of the candidate and internal equity.

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