Machine Learning Engineer

About the role

We are seeking an experienced Machine Learning Engineer to contribute to all phases of the machine learning algorithm development and implementation. You will be joining a team of engineers and scientists who are at the forefront of APL's mission to provide innovative solutions to critical challenges.

Responsibilities

• Design, implement, and evaluate advanced machine learning algorithms to solve challenging real-world planning, perception, coordination, and control problems in support of national defense.
• Develop software pipelines to integrate data streams, simulation environments, and intelligent decision-making algorithms.
• Collaborate closely with the talented team of scientists and engineers in our group and with others across APL.
• Engage directly with sponsors to communicate proposed concepts, solutions, and analysis.

Requirements

• Have a Bachelor’s degree in Mathematics, Physics, Engineering, Computer Science, or a related field.
• Have at least 2+ years of experience in machine learning and data science fields.
• Have at least one year of hands-on experience applying/developing machine learning algorithms using common libraries such as PyTorch or TensorFlow.
• Have strong foundational knowledge in at least two of the following: classification, clustering, deep learning, reinforcement learning, computer vision (object detection and visual tracking), multi-agent systems, or optimization/control theory.
• Have demonstrated experience in working with version control software like Git.
• Have strong, effective communication skills both verbal and written.
• Able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a Secret level clearance.

Qualifications

• Have an MS in Mathematics, Physics, Engineering, Computer Science, or a related field.
• Have 5+ years of experience in designing and implementing AI/ML algorithms for a variety of datasets.
• Have proven experience applying state-of-the-art deep learning techniques to solve distributed resource allocation problems.
• Have hands-on experience building computer vision pipelines for detection, tracking, segmentation, or multi-modal sensor fusion.
• Have experience with modeling and simulation platforms such as AFSIM, Blender, Unity, or Unreal.
• Able to work in high performance computing environments (GPU/CPU clusters).
• Proficient in one or more of the following technology areas: multi-agent reinforcement learning, geometric deep learning, multi-modal sensor fusion, agentic AI.
• Have a track record of writing deployable, production-level code (Python, C/C++) for real-world applications.