Perception Engineer, Staff

Responsibilities

• Own the visual perception pipeline end-to-end, including detection, classification, and tracking of sUAS targets in real time.
• Design and train machine learning models that meet latency and accuracy requirements for edge deployment on Jetson-class hardware.
• Architect and maintain the dataset and simulation pipeline, including data collection, labeling, curation, augmentation, synthetic data generation, and closed-loop retraining based on field performance.
• Optimize inference performance on Jetson platforms, including model pruning, quantization, TensorRT integration, and custom kernel development as required.
• Establish the model evaluation framework and metrics used to assess perception performance under operational conditions.
• Deliver target state information (position, velocity, identity, uncertainty) to the controls subsystem.
• Collaborate with the hardware team on camera, optics, and sensor selection.

Requirements

• 6+ years of professional experience in computer vision or machine learning, including production deployment on edge hardware.
• Demonstrated experience shipping a detection or tracking system under real-world latency, small-object, or adversarial constraints.
• Strong engineering skills beyond modeling, including experience with PyTorch or JAX through to deployed, optimized inference.
• Proficiency in Python for model development and C++ or Rust for deployed inference.
• U.S. citizenship and ability to pass a background check.

Preferred Qualifications

• TensorRT and NVIDIA Jetson deployment experience at production scale.
• Multi-object tracking under challenging conditions.
• Multi-modal sensor fusion experience (EO/IR, radar, acoustic).
• Synthetic data generation and sim-to-real methodologies.
• Prior experience in defense or other safety-critical computer vision applications.
• Active security clearance, or eligibility to obtain one.