Robotics Navigation Engineer

Leidos•Huntsville, AL

3d•Hybrid

About The Position

The Contested Autonomy & Navigation Branch, part of Leidos’ Non-Kinetic Effects Business Area, provides cutting-edge navigation technology for customers who can't rely on GPS alone. This position offers both analytic and hands-on tasks, including development, simulation, analysis, and field testing of navigation algorithms. We perform research, development, and advanced prototyping for DARPA, NASA, Air Force Research Laboratory, Office of Naval Research, and Army Combat Capabilities Development Command engineering centers. You’ll work with other engineers in small teams using spiral or agile development to meet aggressive schedules aimed at near-term field demonstrations.

Requirements

Bachelor’s degree in advanced technical field (electrical engineering, software engineering, aerospace engineering, mechanical engineering, or equivalent) and 4+ years of prior relevant experience or master’s degree with 2+ years of prior relevant experience.
2+ years of relevant experience with one or more sensor fusion algorithms: extended Kalman filters, unscented Kalman filters, particle filters, or factor graphs.
Programming & analysis experience in MATLAB.
Must be a US Citizen
Must be able to obtain and maintain a Secret security clearance after hiring.

Nice To Haves

Master’s or PhD Degree in one of the majors listed above.
Experience with one or more of the sensors listed above, especially inertial sensors.
Experience deploying navigation algorithms to real-time applications.
Experience with computer vision techniques.
Experience with machine learning, particularly convolutional neural networks.
Experience with Linux, C++, and/or Python.
Experience with version control tools, especially Git or Subversion.
Experience with autonomous system development through robotics competitions.
Existing US security clearance (Secret or above).

Responsibilities

Develop algorithms for real-time GPS-denied navigation of robotic platforms.
Navigate a variety of platforms, including aircraft, ships, ground vehicles, and pedestrians.
Use multiple sensor fusion algorithms, including extended Kalman filters, unscented Kalman filters, particle filters, and factor graphs.
Fuse simulated and real-world sensor inputs from inertial sensors, GPS, altimeters, cameras, lidar, odometers, and ranging radios.
Use computer vision techniques like feature matching, SLAM, and visual odometry to extract navigation measurements from imagery.
Work within a team of 3-5 engineers to test algorithms on demonstration hardware.
Travel with the team to demonstrate systems in real-world conditions; typically lasts 1-2 weeks and occurs 3-4 times a year.
Present techniques, solutions, and results to the team and to customers.