We are seeking an entry-level engineer or scientist to support the growth of RF/machine learning capabilities. The selected candidate will contribute in two primary areas: optimization of SAR-related processing for GPU-enabled edge hardware, and support of machine learning workflows including curated dataset development, model training, evaluation, and deployment to edge devices. This role is intended for a candidate with strong technical fundamentals and the potential to grow into a broader RF/ML contributor through mentorship and hands-on experience. Deep SAR expertise is not required. As a member of our team, you will... • Support development and optimization of SAR-related algorithms and processing workflows for execution on GPU-enabled edge hardware. • Assist with profiling, debugging, and improving computational performance to meet edge-device constraints such as latency, memory, throughput, and power. • Build, organize, and maintain curated datasets for machine learning training, validation, and testing. • Develop and apply data preprocessing, labeling, and quality-check workflows to prepare data for analysis and model development. • Train, evaluate, and help refine machine learning models for deployment in edge or resource-constrained environments. • Support integration and deployment of algorithms and trained models onto edge computing platforms. • Collaborate with senior staff to transition prototypes into robust, testable implementations. • Document technical approaches, results, implementation details, and performance tradeoffs. • Work closely with mentors and team members to grow technical depth in RF, SAR, machine learning, and edge deployment applications. • Contribute to the team's emerging RF/ML capabilities through applied development, experimentation, and technical learning. Qualifications You meet our minimum qualifications if you have... • Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or relevant field. • Foundation in signal processing, linear algebra, and related applied mathematical methods. • Programming experience in Python, C++, or similar languages for technical computing, data processing, or algorithm development. • Familiarity with basic machine learning workflows, including data preparation, model training, evaluation, and performance assessment. • Ability to work with raw and processed data to create organized, curated datasets for analysis and model development. • Interest in performance optimization of computational pipelines, including familiarity with GPU or parallel computing concepts. • Awareness of edge or embedded computing constraints such as memory, latency, throughput, and power limitations. • Strong analytical, problem-solving, and communication skills. • Willingness to learn RF, SAR, and edge-deployed ML methods through mentorship and hands-on work. • Are able to obtain an Interim Secret Clearance by your start date and can ultimately obtain a TS/SCI. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information; eligibility requirements include U.S. citizenship. You'll go above and beyond our minimum requirements if you... • Experience with GPU programming, accelerated computing, or performance optimization tools and frameworks. • Exposure to deploying software or machine learning models on embedded or edge computing platforms. • Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or similar toolkits. • Exposure to RF systems, remote sensing, image formation, SAR, or related sensing modalities. • Experience with data curation, labeling, preprocessing, or dataset management for machine learning applications. • Experience working in Linux-based development environments. Minimum Rate $85,000 Annually Maximum Rate $165,000 Annually