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Senior AI/ML Engineer

  • Springfield, Virginia

Key Responsibilities

  • Develop and refine advanced machine learning solutions to identify, classify, and analyze patterns and activities across complex sensor datasets.

  • Lead the full ML development lifecycle, including data preparation, model training, validation, performance tuning, and deployment into mission-focused environments.

  • Collaborate with technical researchers, scientists, and mission specialists to understand unique data challenges and develop effective AI/ML solutions.

  • Build scalable, reliable Python applications following software engineering best practices, with an emphasis on maintainability, testing, and documentation.

  • Assess model accuracy, reliability, and overall effectiveness, identifying opportunities to improve performance across varying datasets and operational conditions.

  • Incorporate machine learning models into established software systems and analytical tools, ensuring successful integration and operational readiness.

  • Provide technical guidance to less experienced engineers through mentorship, code reviews, and the development of consistent engineering practices.

  • Support technical evaluations, solution design, and technology selection by assessing different machine learning methodologies and architectures.

  • Communicate technical findings, project progress, and recommendations through written reports, presentations, and discussions with program leadership and government stakeholders.

Required Qualifications

  • Active Top Secret clearance with eligibility to obtain SCI access and a CI Polygraph.

  • Bachelor's degree in Computer Science, Engineering, Physics, Mathematics, Data Science, or a related STEM discipline. Master's degree or PhD preferred.

  • At least 7 years of professional machine learning experience, including hands-on development and implementation of AI/ML solutions in production or operational settings.

  • Strong understanding of deep learning techniques, including convolutional neural networks (CNNs), transformer architectures, computer vision, and object detection methodologies.

  • Advanced Python development skills and practical experience using frameworks such as PyTorch, TensorFlow, or comparable ML technologies.

  • Experience designing and managing end-to-end machine learning workflows, including data processing, labeling, model development, testing, and deployment.

  • Ability to partner with researchers and technical subject matter experts to convert complex scientific or operational requirements into practical machine learning applications.

  • Previous experience providing technical leadership, mentoring engineers, reviewing code, and promoting software development best practices.

  • Excellent verbal and written communication skills, with the ability to explain complex technical concepts and present findings to both technical and nontechnical audiences.