Autonomy Software Engineer

MORSE is looking for an Autonomy Software Engineer to research, develop and prototype novel autonomy software to enable pre-mission planning and operation of novel aircraft and other autonomous systems. MORSE is seeking an aeronautical, aerospace, mechanical, or electrical engineer in optimization, estimation theory, and/or guidance, navigation and control (GNC) algorithms. Responsibilities will include autonomy development from conceptualization, including the selection and evaluation of sensors, implementation, including software development, and evaluation, including data analysis. The role will involve developing and testing code in a simulation and HWIL environment as well as field tests of the implemented autonomy software. The ideal candidate will have a strong foundation in physics, math, statistics, and computer science, as well as experience handling electronic hardware and machine learning. The candidate will work with a multidisciplinary team in an agile environment to rapidly design, prototype and test autonomous systems. Responsibilities:

• Research, develop, and prototype novel autonomy software and algorithms for autonomous systems
• Develop and evaluate autonomy software from conceptualization to implementation, including selection and evaluation of sensors, software development, and data analysis
• Design, develop, and test algorithms for autonomous systems, including sensor fusion, guidance, navigation, and control
• Develop and test code in simulation and Hardware-In-the-Loop (HWIL) environments, as well as participate in field tests of implemented autonomy software on vehicles and systems
• Collaborate with a multidisciplinary team in an agile environment to rapidly design, prototype, and test autonomous systems

• SHIP REQUIRED or the ability to obtain a U.S. Security Clearance.
• The candidate must have experience developing real-world solutions with computational constraints, measurement errors, and modeling uncertainty
• 5+ years of Autonomy, Guidance, Navigation and or Controls experience
• Experience with developing both algorithms and the simulations for test and validation
• Expertise in positioning, navigation, and timing, particularly for aircraft
• The ideal candidate will have experience working on complex, multi-disciplinary R&D programs
• BS. or M.S. (preferred) in Aeronautical/Aerospace, or Electrical Engineering (Control or Signal Processing focus) or equivalent degree/major, * Expertise in sensor fusion such as Kalman filtering and experience with multiple sensing modalities
• Experience with designing and integration of autonomy hardware (sensors, flight controllers)
• Experience with C++ and Python software languages and software design best practices.
• Experience with sensor modeling, simulation, and performance analysis
• Experience in ML model development and deployment using open-source tooling such as PyTorch and ONNX
• Ability to lead a small multi-disciplinary team is a plus

MORSE Corp’s salary range for this role carefully considers a wide range of compensation factors, including but not limited to, prior experience, education, skills and expertise, location, internal equity, and other factors that are job related and consistent with business need. Therefore, final offer amounts may vary from the amount stated. Depending on role eligibility, total compensation may also include bonus, stock, 401(k) match, paid time off, medical, dental, vision and life insurance.

Employees also receive 10 paid holidays per year. MORSE maintains an “open” leave policy that does not restrict exempt, regular full-time employees to a specific number of paid sick or vacation days. However, this policy is not an “unlimited” paid leave policy.

MORSE Corp is an employee owned, small business based in Cambridge, MA, Arlington, VA, and Seattle, WA with a history of fielding cutting-edge technology. MORSE boasts a specially selected team of scientists, engineers, and software developers to deliver best-in-class technical solutions that solve difficult multidisciplinary problems faced by the US National Security Ecosystem.