Machine Learning Engineer

As a result of program growth, the Electronic Warfare Division is looking for a mid‑level Machine Learning Engineer to support remote sensing programs in Beavercreek, OH. The role focuses on developing advanced sensor exploitation and machine‑learning solutions for remote sensing modalities such as SAR/RF, acoustic, EO/IR, and LIDAR.

• Work with teams to research, design, and develop sensor exploitation systems including signal processing, automatic target recognition (ATR), and target signature modeling.
• Develop ATR algorithms using Python, MATLAB, and C++ for real‑world applications and leverage state‑of‑the‑art AI/ML tools to improve performance.
• Collaborate with customers to address challenging mission requirements, research and develop new capabilities, and improve existing systems.
• Develop performance models and algorithms for new and/or existing target recognition solutions.
• Perform high‑level software development using Python, C++, and MATLAB including design, development, troubleshooting, and debugging.
• Exercise strong written and oral communication skills, including generating documentation, reporting to customers, and delivering presentations.

• Bachelor’s degree with 4+ years of machine learning development experience or Master’s degree with 2+ years of experience (Doctorate possible).
• Active SECRET clearance or higher, with ability to obtain TS/SCI clearance.
• U.S. citizenship required.
• Expert‑level programming in Python with libraries such as XGBoost, PyTorch, Scikit‑Learn, etc.
• Deep learning experience with one or more current LLMs.
• Effective written and oral communication of technical solutions.
• Familiarity with Num Py, Sci Py, MATLAB, etc., for data evaluation and sense making.
• Familiarity with Linux and Windows operating systems.

• Strong C/C++ development skills for Linux and Windows, including high‑performance solutions.
• Experience with Git Lab, Jira, or similar agile project management tools.
• Experience developing ML solutions with noisy and uncertain data.
• Experience generating synthetic data and training/testing algorithms on synthetic data.
• Experience performing model verification and validation.
• Previous experience with sensor exploitation algorithms such as Combat Identification (CID), tracking, detection, fusion, or pattern‑of‑life algorithms and/or models.
• Strong understanding of statistics.
• Basic understanding of signal processing and applying ML to time‑series data sets.

All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.