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Applied Intuition NewPosted 15h ago

Perception Engineer, Autonomy (Air Domain)

Location

Fort Walton Beach, FL, United States

On-site

Contract

Permanent

Full-time

Salary

$150–185k

Gross per year

Experience

Not specified

Job summary

Responsibilities

As a Perception Engineer, you will help build the perception layer of an autonomy stack for uncrewed air vehicles. The team turns noisy, intermittent data from many sensors and teammates into a reliable picture of the airspace.

  • 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

What they're looking for

  • BS/MS in Electrical, Aerospace or Mechanical Engineering, Computer Science, Robotics, or a related field, plus 3+ years building perception or estimation software for autonomous…
  • Strong modern C++ (17/20) for real-time, performance-critical code on Linux. Comfortable with linear algebra libraries (e.g. Eigen) and profiling.
  • Solid grounding in state estimation: Kalman filter variants (EKF/UKF), multiple-model filters (IMM), and covariance and uncertainty handling.
  • Experience with multi-target tracking and sensor fusion: data association, track management, and fusing heterogeneous sensors that report intermittently and with noise.
  • Working knowledge of machine learning for prediction, including sequence models (RNN/LSTM, transformers), training pipelines, and evaluating models on held-out data.

Tech stack

Read the full job posting

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