Machine Learning Engineer

LeidosBeavercreek, OH
Onsite

About The Position

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. As a Machine Learning Engineer, you will apply your skills to a wide variety of problems and datasets primarily focused on remote sensing (SAR/RF, acoustic, EO/IR, and LIDAR) applications. You will work with a multi-disciplined engineering team (Electrical Engineers, Physicists, Computer Scientists, etc.) to design, develop, simulate, and integrate components into sensor systems and data fusion solutions based on given project requirements. Current projects include, but are not limited to, detection, tracking, data fusion, and classification. This is an exciting opportunity to use your experience to help the Combat Identification (CID) team perform advanced research and development for target recognition solutions using synthetic and measured data AI/ML training techniques for multiple sensor modalities. We are looking for a qualified candidate to bring technical excellence, rigorous software engineering principles, and creativity to our programs. You will have the opportunity to pursue growth in new technology areas. This position requires 100% onsite job duties due to the sensitive nature of this work.

Requirements

  • Bachelor’s degree with 4+ years of prior machine learning development experience or Master’s degree with 2+ years of prior machine learning development experience.
  • Possess an active SECRET clearance or higher, with an ability to obtain a TS/SCI clearance.
  • US citizenship required.
  • Expert-level programming ability in Python including libraries such as XGBoost, PyTorch, Scikit-Learn, and others.
  • Deep learning experience with one or more current LLMs.
  • Ability to effectively communicate, both written and orally, technical solutions to coworkers, teammates, and customers.
  • Familiarity with common data processing tools such as NumPy, SciPy, MATLAB, et al. for data evaluation, quality determination, and sensemaking.
  • Familiarity with Linux and Windows operating systems.

Nice To Haves

  • Strong C/C++ development skills for both Linux and Windows environments including high-performance solutions.
  • Familiarity with GitLab and/or Jira issue tracking and agile project management, or similar tools.
  • Experience in developing machine learning solutions with noisy and uncertain data.
  • Experience generating synthetic data in addition to training and/or testing machine learning algorithms based on synthetic data.
  • Experience performing model verification and validation.
  • Previous experience developing 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 familiarity with applying machine learning to time-series data sets.

Responsibilities

  • 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.
  • Leverage state-of-the-art AI/ML tools and methods to improve performance of ATR systems.
  • Collaborate with our customers to address challenging mission requirements by researching and developing new capabilities as well as making improvements to existing systems.
  • Develop performance models and algorithms for new and/or existing target recognition solutions.
  • Perform high-level software development functions using Python, C++, and MATLAB including design, development, troubleshooting, and debugging software programs.
  • Exercise strong written and oral communication skills.
  • Aspects of the position include generating written software and internal documentation as well as reporting to the customer.
  • Oral presentations to the customer and the larger research community are required.

Benefits

  • competitive compensation
  • Health and Wellness programs
  • Income Protection
  • Paid Leave
  • Retirement
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