Job Summary:
Johns Hopkins Applied Physics Laboratory is seeking an experienced Machine Learning Engineer to contribute to the development and implementation of machine learning algorithms for national defense applications. The role involves designing advanced algorithms, developing software pipelines, and collaborating with a multidisciplinary team to solve complex real-world problems.
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.
• Work with technologies and concepts at the cutting edge of AI, including but not limited to: deep reinforcement learning, foundation models, large language models, convolutional/recurrent/graph neural networks, computer vision, and physics-based modeling and simulation tools.
• 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.
Qualifications:
Required:
• 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.
• Are able to obtain an Interim Secret level security clearance by your start date and can ultimately obtain a Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.
Preferred:
• 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.
• Are comfortable working in high performance computing environments (GPU/CPU clusters).
• Have proficiency 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.
Company:
The Johns Hopkins Applied Physics Laboratory (APL) is a not-for-profit university-affiliated research center (UARC) that provides solutions to complex national security and scientific challenges with technical expertise and prototyping, research and development, and analysis. Founded in 1942, the company is headquartered in Laurel, USA, with a team of 5001-10000 employees. The company is currently Late Stage.