Robotic Software Engineer, Perception

Washington, District of Columbia, United States

Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy.

Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.;
San Diego;
Ft. Walton Beach, Florida;
Ann Arbor, Michigan;
London;
Stuttgart;
Munich;
Stockholm;
Bangalore;
Seoul; and Tokyo. Learn more at

As a Perception Autonomy engineer, you will be pivotal in developing, integrating, and maintaining real-time sensor software solutions deployed across a range of heterogenous autonomous vehicles and different domains (e.g., land, air, sea, and space). You will work with a team to continuously add capability and demonstrate the solution to customers in real-world scenarios on a variety of hardware platforms. Your responsibility will primarily be designing, developing, and rapidly integrating AI/ML sensor algorithms to interface across different platforms, ingest relevant mission information, and support the autonomy team’s mission objectives.

This work includes developing autonomous sensor controllers to optimally fuse information between state-of-the‑art sensor systems, such as EO, IR, acoustics, radar, and RF.

• Develop, integrate, and adapt cutting‑edge AI/ML algorithms running on the perception autonomy stack to collect relevant information across a suite of platform sensors
• Create interfacing software to autonomously control sensors (e.g., EO, IR, acoustics, radar, and RF)
• Collaborate across the sensor, tracking, and autonomy teams to ensure seamless deployment of heterogeneous platform swarms in on‑site DoD testing and demonstration events
• Deploy containerized solutions to embedded Linux devices, leveraging computer‑in‑the‑loop testing and profiling, and efficiently collecting performance data
• Interact with the DoD customer to understand their use cases, requirements, and triage needs during field events to deliver a superior customer experience
• Work closely with our existing team to internally triage technical problems and scope
• Carefully communicate and document ongoing work to ensure internal flexibility in a fast‑paced environment as well as clarify progress with external customers
• Drive execution of simulation tooling to playback sensors, platforms, and autonomy in post processing field test analysis
• Implement improvement plans for future integration efforts based on simulation analysis and customer feedback

• MS or PhD in Electrical Engineering, Computer Engineering, Robotic Engineering, Computer Science, Optimization, or equivalent OR 5+ years of relevant experience working with sensor algorithms, hardware, and HIL software integration
• Experience with multiple sensor modalities (e.g., EO, IR, lidar, radar, sonar, acoustics, etc.) Core understanding of sensor physics and sensor control parameters
• Experience training and deploying ML algorithms (python, pytorch, tensor flow) onto integrated systems (onnx, C++ models)
• Familiarity with tracking basics (e.g., Kalman filters) and optimal sensor fusion
• Experience working comfortably in Linux and Docker
• Prior experience with remote software development, ability to handle and process large datasets, and learn new software and algorithms as needed with little supervision

• Must be willing to travel as projects requires, usually for SW/HW integration and/or demonstrations; estimated average travel is every 1‑2 months for 2‑5 days (10‑20%)
• Travel‑adverse candidates are encouraged to inquire about relocation assistance to HQ in Poway, CA

• Must be a U.S. Citizen
• Must…