Senior Perception Algorithms Lead

Duties and Responsibilities

• Lead development of perception algorithms for detection, tracking, and classification using RF, EO/IR, and other sensor modalities
• Design and implement multi-sensor fusion pipelines for robust state estimation and object tracking
• Develop and train models for feature extraction and classification directly from sensor data
• Apply probabilistic methods, statistical inference, and data-driven modeling techniques to noisy, real-world datasets
• Implement and optimize algorithms using modern computational frameworks and hardware acceleration
• Define perception outputs (detections, tracks, classifications, confidence metrics) for downstream system consumers
• Validate performance using real-world data, simulation, and test events

Requirements

• Typically requires a bachelors degree, masters degree or PhD in engineering or a related technical discipline from an accredited institution and progressive engineering experience as follows; fifteen or more years of experience with a bachelors degree, thirteen or more years of experience with a masters degree, or ten or more years with a PhD.
• May substitute equivalent engineering experience in lieu of education.
• Strong background in probabilistic methods (e.g., Bayesian inference, filtering, estimation theory)
• Proficiency in Python and/or C++ for algorithm development
• Experience using modern numerical and computational libraries (e.g., NumPy, SciPy)
• Experience implementing and training models using frameworks such as **PyTorch, TensorFlow, or similar**
• Experience working with real sensor data (noise, calibration, artifacts, edge cases)

Qualifications

• Experience with multi-target tracking, data association, or sensor fusion architectures
• Experience with GPU acceleration (CUDA, cuDNN, or similar)
• Familiarity with large-scale data pipelines and dataset curation
• Experience with both model-based and learned approaches for perception problems
• Experience with RF, radar, EO/IR, or other sensing modalities
• Experience optimizing models for deployment (quantization, pruning, performance tuning)

Additional Attributes

• Ability to operate across theory, implementation, and system integration
• Strong ownership of technical solutions from concept through deployment
• Effective communication across multidisciplinary engineering teams
• Focus on delivering robust, testable, and fieldable solutions
• Ability to obtain and maintain a DoD security clearance is required