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The Contested Autonomy and Navigation Branch at Leidos develops cutting-edge alternative navigation and autonomy technologies for environments where GPS alone cannot be trusted. Based in Huntsville, AL, this role combines algorithm development, simulation, integration, and real-world field testing of autonomous systems for customers including DARPA, NASA, AFRL, ONR, and the U.S. Army.

You'll work on small, fast-moving engineering teams developing and demonstrating advanced capabilities on aircraft, ground vehicles, pedestrians, and maritime platforms. This is a highly hands-on role where you'll see your work move rapidly from concept to field demonstration and operational deployment. Unlike large production programs, this team focuses on rapid prototyping and transitioning advanced autonomy capabilities from research into operational demonstrations. Engineers on this team are expected to take ownership of technical problems from initial concept through field demonstration and customer evaluation. Engineers regularly participate in field experiments and flight tests, directly supporting customer demonstrations of new autonomy capabilities.

Primary Responsibilities:

• Develop, integrate, and analyze state estimation and multi-sensor fusion algorithms, including
  • Extended Kalman Filters
  • Unscented Kalman Filters
  • Particle Filters
  • Factor Graphs
• Develop, integrate, and analyze computer vision perception and localization techniques including
  • Feature extraction/matching
  • Optical flow/visual odometry
  • Image correlation
  • Simultaneous Localization and Mapping (SLAM)
  • Machine learning approaches for all of the above
• Development is performed primarily in MATLAB, Python, C++, ROS, and Linux-based environments.
• Develop and utilize simulation testbeds to support algorithm testing and assessment
• Travel with your team to demo your system to the customer on a variety of platforms, including aircraft, ground vehicles, pedestrians, and naval ships. Testing trips typically last for 1-2 weeks and occur 3-4 times a year.

Minimum Requirements:

• Bachelor's degree in computer engineering, Electrical Engineering, Computer Science, Aerospace Engineering, Mechanical Engineering, or equivalent with 2+ years' experience or Master's with < 2 years' experience
• Must be a US Citizen
• Must be eligible to obtain and maintain a U.S. Secret security clearance.
• Experience with MATLAB, Python, or C++ for algorithm development and analysis. Most early-stage algorithm development and analysis is currently performed in MATLAB. Background in robotics, controls, estimation, or autonomous systems
• Experience with either sensor fusion/estimation algorithms (e.g. Kalman Filters, Particle Filters, or Factor Graphs), or with computer vision algorithms (for instance OpenCV). If you have experience with both sensor fusion and computer vision that's even better!

Preferred Skills:

• Experience working with various sensor types (Inertial Measurement Units, GPS, cameras, LiDAR, etc.)
• Experience with the Robot Operating System (ROS) and the OpenCV computer vision library
• Experience with interface communication standards / protocols including RS232, RS422, TCP/IP, and UDP to communicate with various sensors
• Experience with autonomous system development through robotics competitions
• Experience with the Linux operating environment
• Experience using version control tools (Git, Subversion, etc.).
• Experience with AI/Machine Learning for computer vision or robotics applications

NKE

If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares.

The Leidos pay range for this job level is a general guideline onlyand not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.