Radar Systems Engineer

Are you interested in developing advanced radar systems to make an impact on our nation’s defense? Do you want to be part of an enthusiastic team dedicated to advancing the state of the art in radar systems? How about contributing to the design and test algorithms for defense against missiles, including but not limited to hypersonics? If so, we’re looking for someone like you to join our team at APL. We are seeking a creative and highly motivated problem solver to help us develop and analyze advanced radar systems within the Air and Missile Defense Sector, the Sensor Systems Engineering Group (A2B). You will work with other APL engineers as well as outside prime contractors and government sponsors and engage with a hardworking and enterprising team of scientists and engineers working to develop high‑impact solutions for the nation’s defense. Responsibilities Conduct analysis of radar systems utilizing existing high‑fidelity radar systems to understand capabilities and limitations under highly variable operational conditions. Research and develop realizable solutions to gaps and opportunities identified through modeling, simulation, and analysis. Provide insightful documentation on analysis findings and new concepts. Interact with sponsors to understand program priorities, share analysis results, and introduce new concepts. Participate in design reviews, technical interchanges, working groups, and program status meetings as a presenter or reviewer. Participate in meetings and collaborations at Navy and vendor locations. Have the opportunity to develop and propose ideas for APL internal research and development funding. Minimum Qualifications Bachelor of Science degree in Physics, Mathematics, Electrical Engineering, Computer Science, Computer Engineering, or related technical field. At least 1 year of experience in aerospace, hypersonics, radar, or RF systems. Familiarity with Python, MATLAB, MATLAB toolboxes, and Microsoft Office products. Excellent interpersonal skills and ability to effectively interact with sponsors, management, and working‑group team members in a fast‑paced environment. Ability to obtain an Interim Secret clearance by start date and ultimately a Secret level clearance; U.S. citizenship required. Preferred Qualifications Master’s degree in one of the fields listed above. More than 2 years of experience in aerospace, hypersonics, radar, or RF systems. Experience managing and manipulating large data sets and applying various machine‑learning techniques. Experience scripting and coding in multiple languages; applying signal processing, machine learning, stochastic processes, AI, or related areas to algorithm development for phased‑array, dense‑medium, digital radar, or multi‑static radar. Current Secret clearance with the ability to obtain higher‑level clearances. Compensation & Benefits Minimum Rate: $85,000 Annually Maximum Rate: $195,000 Annually APL offers a 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. Additional compensation such as bonuses, sign‑on bonus, relocation benefits, locality allowance, or discretionary payments may be provided at the discretion of internal policy and/or contractual designation. Equal Employment Opportunity All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact View email address on click.appcast.io. #J-18808-Ljbffr Johns Hopkins Applied Physics Laboratory