Clearance-Eligible Signal Processing & ML Engineer

The Johns Hopkins University Applied Physics Laboratory; Laurel (MD); On-site; USD 85,000 - 165,000; Full time

Job summary

The Johns Hopkins University Applied Physics Laboratory (APL) seeks motivated engineers, physicists, mathematicians, and computer scientists to advance sensor algorithms for defense applications. You will develop large-scale EM/radar simulations and prototype signal processing methods for deployment in national security missions.

Role involves optimizing code on massive compute clusters, applying machine learning to large datasets, and collaborating across disciplines. U.S.

Qualifications

• BS in a relevant engineering or related discipline.
• Strong problem solving/analytical skills.
• Excellent verbal, written and presentation communication skills.
• Able to collaborate with colleagues from varied areas and experience levels.
• Eligible for Interim Secret and ultimately Secret clearance; U.S. citizenship required.

Responsibilities

• Develop large scale simulations of electromagnetic fields and radar systems.
• Optimize algorithms to run on multi-million-dollar computational clusters.
• Prototype novel signal processing algorithms for deployment by the military.
• Use machine learning techniques to augment capabilities.
• Gain a deep understanding of electromagnetic phenomena for practical use and exploitation.
• Apply data science and machine learning to complex, large-scale datasets.

Skills

Problem solving

Communication

Collaboration

Citizenship clearance eligibility

Education

BS in Electrical Engineering, Computer Science, Aerospace Engineering, Computer Engineering, Systems Engineering, Mechanical Engineering, Engineering Physics, Applied Physics, Applied Math or related discipline

Job description

The Johns Hopkins University Applied Physics Laboratory (APL) seeks motivated engineers, physicists, mathematicians, and computer scientists to advance sensor algorithms for defense applications. You will develop large-scale EM/radar simulations and prototype signal processing methods for deployment in national security missions.

Role involves optimizing code on massive compute clusters, applying machine learning to large datasets, and collaborating across disciplines. U.S.