Perception Engineer, Autonomy (Air Domain)
About The Position
As a Perception Engineer, you will build the perception layer of an autonomy stack for uncrewed air vehicles, turning noisy and intermittent data from multiple sensors and teammates into a reliable picture of the airspace. The work spans classical state estimation and tracking, sensor fusion, and learning-based prediction, including models that adapt online during an engagement from limited and delayed feedback. You will design and implement real-time C++ algorithms, develop tooling and simulation studies to evaluate them, and take ideas from research prototypes into deployable software. The role calls for fluency in estimation theory and machine learning, rigor in measuring results, and comfort working across research and production. You will develop and integrate algorithms, create sensor-control interfaces, collaborate across teams, deploy containerized solutions to embedded Linux devices, and work with DoD customers during field events. Applied Intuition is an in-office company. Full-time employees are expected to work primarily from an Applied Intuition office five days a week, with flexibility for occasional remote work and schedule adjustments. This expectation does not apply to contractor positions.
Requirements
- 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 systems.
- Strong modern C++ (17/20) skills for real-time, performance-critical Linux code; comfort with linear algebra libraries such as Eigen and profiling.
- Solid grounding in state estimation, including Kalman filter variants (EKF/UKF), multiple-model filters (IMM), and covariance and uncertainty handling.
- Experience with multi-target tracking and sensor fusion, including data association, track management, and fusion of heterogeneous sensors with intermittent, noisy reports.
- Working knowledge of machine learning for prediction, including sequence models (RNN/LSTM, transformers), training pipelines, and evaluation on held-out data.
- Python skills for data pipelines, analysis, and visualization of logged and simulated runs.
- Experience validating algorithms in simulation and with recorded data, including designing experiments, defining metrics, and interpreting results honestly.
- Bachelor's degree in Computer Vision, Computer Science, Electrical Engineering, Robotics, or a related technical field; 2+ years of industry experience.
- Must be a U.S. citizen.
- Must hold or be eligible to obtain and maintain a U.S. security clearance.
Nice To Haves
- Experience with online, real-time learning, including models that adapt during operation rather than only offline training.
- Background in adaptive control or learning-based estimation, such as concurrent learning, Lyapunov-based learning, or Bayesian or recursive least-squares parameter estimation.
- Experience learning from intermittent, delayed, or sparse feedback where ground truth arrives late or only sometimes.
- Experience with behavior and intent prediction for other agents, including non-cooperative or adversarial actors.
- Experience deploying small neural networks in C++ without heavy ML frameworks, under tight latency and compute budgets.
Responsibilities
- Develop, integrate, and adapt AI/ML algorithms on the perception autonomy stack to collect relevant information across platform sensors.
- Create software interfaces to autonomously control sensors, including EO, IR, acoustics, radar, and RF.
- Collaborate with sensor, tracking, and autonomy teams to support deployment of heterogeneous platform swarms during on-site DoD testing and demonstration events.
- Deploy containerized solutions to embedded Linux devices, using computer-in-the-loop testing and profiling and collecting performance data.
- Work with DoD customers to understand use cases, requirements, and triage needs during field events.
Benefits
- Comprehensive health, dental, vision, life, and disability insurance coverage.
- 401k retirement benefits with employer match.
- Learning and wellness stipends.
- Paid time off.
- Equity in the form of options and/or restricted stock units may be included in eligible roles' total compensation.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
