Research Software Engineer – Computational Fluid Dynamics (CFD) & HPC

Analytical Mechanics Associates•Hampton, VA

1d•$95,000 - $110,000

About The Position

Analytical Mechanics Associates (AMA) is seeking a Research Software Engineer to assist a NASA Computational Fluid Dynamics (CFD) code development team in the development, implementation, optimization, and evaluation of both existing and nascent time-integration schemes for complex unsteady flows discretized on static and dynamic unstructured grids. Relevant applications will span the speed range, with physical modeling strategies to include, but not be limited to, unsteady Reynolds-averaged NS (RANS), hybrid RANS-Large Eddy Simulation (HR-LES), Wall-Modeled LES (WM-LES), and Wall-Resolved LES (WRLES) approaches. Both perfect-gas and reacting-gas flows incorporating finite-rate chemistry algorithms are relevant. The successful applicant will join AMA in support of NASA Langley Research Center in Hampton, VA, as part of the Research, Science and Engineering Services (RSES) contract The salary range for this position is $95,000 and $110,000.

Requirements

MS in engineering, applied mathematics, computer science, physics, or equivalent, with strong background in HPC and computational science for large-scale applications.
Demonstrated experience in GPU programming techniques for real-world applications; ability to achieve and demonstrate optimal performance for both memory and compute-bound motifs.
Proficiency with the MPI and CUDA/HIP programming models and the C++ language.
A desire to quickly learn and apply new paradigms relevant to current and emerging architectures, and an eagerness to work in a team environment.
US citizenship or permanent resident status is a bona fide requirement.

Nice To Haves

Previous experience targeting performance portability and the use of programming abstraction models.
Previous experience working with unstructured grids and implicit solution techniques.
Knowledge of fluid mechanics, numerical methods, and/or physical modeling techniques.
Familiarity with other programming languages such as Python and FORTRAN and tools such as git, cmake, debuggers, and queuing systems.

Responsibilities

Develop, implement, and demonstrate computationally-performant implementations of existing and nascent algorithms, targeting GPU-based High-Performance Computing (HPC) systems while retaining performance portability to CPU-based architectures.
Collaborate within a multidisciplinary team, leveraging GPU-based HPC systems and state-of-the-art programming models to realize a sustainable, performance-portable computational toolset for nextgeneration CFD simulations