Johns Hopkins Applied Physics Laboratory · 3 months ago
2026 PhD Graduate Software Engineering/ML/Data Scientist - Intelligence Systems
Johns Hopkins Applied Physics Laboratory (APL) is seeking recent PhD graduates to join their team, focusing on complex research, engineering, and analytical problems that address critical challenges to the nation. The role involves working on projects related to Machine Perception, Intelligent Systems, Reasoning for Autonomy, Software Engineering, ML Operations, and Data Science in a collaborative team environment.
EducationUniversities
Responsibilities
Work with dedicated team members charged with developing and delivering solutions that support national priorities
Work within a team environment and apply your skills to projects and tasks in areas such as Machine Perception, Intelligent Systems, Reasoning for Autonomy, Software Engineering, ML Operations, and Data Science
Qualification
Required
Possess a PhD in Computer Science, Mathematics, Engineering, or related technical field
Are able to obtain an Interim Secret clearance by your start date and can ultimately obtain a Top Secret level security clearance. If selected, a government security clearance investigation will need to be conducted and the requirements met for access to classified information. Eligibility requirements include U.S. citizenship
Benefits
Robust education assistance program
Unparalleled retirement contributions
Healthy work/life balance
Comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development
Company
Johns Hopkins Applied Physics Laboratory
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.
Funding
Current Stage
Late StageTotal Funding
unknownKey Investors
U.S. Department of Homeland Security
2023-01-17Grant
Leadership Team
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2025-12-20
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2025-12-19
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