Engineer VII

General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable Unmanned Aircraft Systems and emerging Advanced Programs for multiple customers.
We have an exciting opportunity for a Project Engineer integrated product team (IPT) leader to join our Agile Mission Systems (AMS) team here in San Diego in support of multiple advanced projects focusing on electromagnetic spectrum dominance.

We are seeking a Perception Algorithms Lead to develop and deploy advanced algorithms for sensing, detection, tracking, and classification across multi-modal sensor systems. This role focuses on extracting structured information from raw sensor data under real-time and resource-constrained environments.  This lead will assist Perception Systems in transforming data from a variety of sensors—both internally developed and externally sourced—into a coherent, fused understanding of the environment.  These perception outputs (e.g., detections, tracks, and classifications) are provided as structured inputs to downstream mission systems that perform higher-level functions such as navigation, task execution, and mission behavior.

The ideal candidate combines strong foundations in signal processing, estimation, and applied mathematics with experience implementing modern computational and data-driven approaches for perception systems.

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
• Deploy algorithms in real-time and embedded environments with strict latency and compute constraints
• Define perception outputs (detections, tracks, classifications, confidence metrics) for downstream system consumers
• Validate performance using real-world data, simulation, and test events ​​​​​​​
• Mentor engineers and establish best practices across perception algorithm development

We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.

 

• 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)
• Preferred 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