Scientific Programming and Machine Learning Engineer

Description

Leidos is looking for scientific programmers, computer scientists, or mathematicians with an Artificial Intelligence/Machine Learning (AI/ML) background to support our growing work in the Eglin office. In this capacity you will propose, design and develop new Artificial Intelligence/Machine Learning (AI/ML) tools to support the design and analysis of high speed weapons systems. Leidos presently uses deep learning Artificial Neural Networks (ANN)s for the purpose of providing fast running models, and thus you would maintain existing ANN's in addition to developing new ANN based fast running models.

In this position you will work directly with accomplished aerospace, mechanical, and electrical engineers both internal to Leidos and with external customers. You will need to effectively propose new research ideas to the customer, execute on the research, and present verbal and written status reports. The ability to publish research papers in academic journals and present conference papers is a requirement.

Apply your skills to develop advanced AI/ML techniques to model aerodynamic, structural and thermal phenomena. Perform research that develops new techniques to improve the modeling of emerging high speed weapons systems. Develop tools that enable the future of Digital Engineering. Join a team that is helping to secure the nation.

Be part of a close knit team and work with world class experts. The Aerophysics group operates in a small team environment where individual creativity is rewarded and continuous learning is the norm. Our engineers typically work directly with DOD personnel and regularly interact with contracting teams from Lockheed Martin, Boeing, Northrup Grumman, etc. The Destin-Fort Walton Beach-Niceville area is home to world famous beaches and a relaxed 'salt-life' lifestyle.

Experience Level: BS and 12+ years of experience required. MS or PhD in Mathematics, Engineering, Computer Science, Machine Learning preferred.

Citizenship: Must be a US Citizen and have an active SECRET clearance.
Candidate must be located in or willing to relocate to the Eglin AFB, FL area
Machine Learning: Experience with POD or PCA, scikit, TensorFlow, Keras, PyTorch, or equivalent is required
Programming Skills: Python, C/C++, Matlab, Fortran, Linux, Bash scripting
Engineering Skills: Preferred candidates will be familiar with at least one of the following Modeling and Simulation disciplines: Computational Fluid Dynamics (CFD), heat transfer, dynamics, controls, Finite Element Analysis (FEA), structural/materials engineering.
Communication Skills: Successful candidates should be able to effectively communicate with Leidos aerodynamics, airframe, and guidance and control personnel, and interact daily with customers, team members and end users. Must develop a clear understanding of customer goals and objectives and shape work activities to satisfy them. Must present both verbal and written status on a regular basis, and prepare manuscripts for publication at technical conferences and for professional journals.

Desire Skills:
Candidates with the skills described below will be given preference.
Programming: OOP, Numpy, Scipy, LAPACK, BLAS, MPI, Git, CUDA
CFD: CART3D, Kestrel, FUN3D, US3D, CFD++, Pointwise
FEM: ANSYS, Sierra Tool suite, LS-Dyna
CAD: Solidworks
HPC: PBS or Slurm or other demonstrated skills on utilizing HPCs

LInC

Electronic Warfare

Original Posting Date:

2024-10-10
While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $122,200.00 - $220,900.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.