Robotic Software Engineer, Perception

Confirmed live in the last 24 hours

Applied Intuition

Compensation

$140,000 - $220,000/year

San Diego, California, United States

Remote

Posted January 14, 2026

Job Description

About Applied Intuition

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 applied.co.

We are an in-office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving earlier when needed to accommodate family commitments.

About the role

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.

At Applied Intuition, you will:

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

We're looking for someone who has:

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, tensorflow) onto integrated systems (onnx, C++ models)
Familiarity with tracking basics (e.g., Kalman filters) and optimal sensor fusion
Experience working comfor

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