Autonomy Engineer

    • Laurel, MD

Are you inspired by the boundless potential of deep learning and artificial intelligence?

Are you passionate about applying fundamental research in AI to develop autonomous systems that work independently and alongside their human teammates for life-saving, real-world applications?

If you envision such a future, and want to work hard to integrate your ideas into successful products, we want you to join APL.

We are seeking a research scientist interested in fundamental and applied machine learning research. We want to find an intellectually curious person with a desire for building solutions to next generation problems. You'll be joining a team of interdisciplinary scientists that bridge the gap between the academic and applied sides of research, and who share a vision of building autonomous systems to ensure national security, effective disaster relief, quick and efficient emergency response, and other high-impact customer needs.

As an Autonomy Engineer, you will...

  • Primarily design, evaluate, and implement both novel and known algorithms to challenges in autonomous perception, sensor fusion, and reasoning systems geared toward providing autonomous solutions for our customers
    Collaborate with software engineers to implement the state-of-the-art in autonomy into software for robust systems
  • Craft deep learning approaches to solve problems for autonomy, computer vision, detection/classification, and tracking
  • Fuse input modalities into an autonomous system than can reason and act intelligently in its environment
  • Develop creative ML solutions and work to deploy them rapidly
  • Keep apprised of the latest AI research and collaborate with research scientists to implement cutting-edge research into applied projects


You meet our minimum qualifications for the job if you have...
  • A Master's degree in Computer Science, Mathematics, or a related discipline
  • Strong technical ability in mathematics, statistics, and programming
  • Experience applying machine learning to real world problems
  • Competence working in one or more of the following languages (Python, C , Java)
  • Experience with at least one main stream deep learning framework (e.g. Tensorflow, Pytorch, Caffe, etc.)
  • Excellent ability to communicate technical ideas succinctly and clearly to both technical and non-technical audiences
  • Are willing and able to [special working conditions like travel, schedule, lifting/walking]
  • Are able to obtain a Secret level security 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

You'll go above and beyond our minimum requirements if you have...
  • A Ph.D. degree in Computer Science, Mathematics, or a related discipline
  • Excellent Python coding skills and 2 years of experience working in deep learning frameworks
  • Publications in machine learning conferences and/or journals
  • A proven track record in algorithm design and autonomous system design
  • A current Secret or Top Secret security clearance

Why work at APL?

The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. With a wide selection of challenging, impactful work and a robust education assistance program, APL promotes a culture of life-long learning. Our employees enjoy generous benefits and healthy work/life balance. APL's campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities atwww.jhuapl.edu/careers.

APL is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, disability status, veteran status, or any other characteristic protected by applicable law.

APL brings research applications to life in the space science, asymmetric operations, force projection, and air and missile defense categories, pioneering solutions to push scientific boundaries.

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