Senior Algorithm Engineer

SRC, Inc. is currently seeking a Senior Algorithm Engineer to lead the development of radar, RF, and multi-sensor processing algorithms supporting ISR, EW, and advanced sensing missions. This role is for an engineer who works from the physics and the mathematics outward: understanding what a sensor can and cannot measure, deriving the processing that extracts the most information from that measurement, and proving the performance with evidence a customer will accept. You will lead algorithm development tasks of moderate scope, identify technical approaches to problems that do not have off-the-shelf answers, guide the technical efforts of less experienced engineers, and contribute to proposals and customer engagements. The work spans detection and estimation theory, adaptive signal processing, coherent imaging, tracking and fusion, and increasingly the hybrid space where learned methods and model-based processing meet. The successful candidate has depth in the theory and experience applying it to real recorded data.
What You'll Do
Support and may lead the development, analysis, and validation of radar and sensor processing algorithms of moderate scope, from mathematical formulation through implementation and performance characterization
Identify technical problems and shortfalls in existing processing chains and define approaches to address them
Develop and apply advanced processing techniques such as adaptive beamforming, space-time adaptive processing, clutter suppression, waveform design and optimization, interference mitigation, and coherent imaging
Analyze complex recorded data to characterize phenomenology, diagnose anomalies, and establish what the achievable performance actually is versus what theory predicts
Build and maintain high-fidelity modeling and simulation to support algorithm development, trade studies, and Monte Carlo performance prediction
Define performance metrics and test methodology, and produce defensible analysis of algorithm performance including sensitivity to environment, geometry, and system parameters
Support the transition of algorithms from prototype to real-time and embedded implementations, working with software and hardware engineers on fixed-point effects, latency, throughput, and processing budgets
Evaluate where learned methods add value over model-based processing, and integrate them where the evidence supports it
Provide the technical guidance of less experienced engineers and develop their analytical judgment
Contribute to proposals and white papers, and assist in presenting technical findings and recommendations to customers
Exercise independent technical judgment on approach selection and communicate the tradeoffs clearly to program leadership
What You'll Bring
Bachelor’s degree in degree in Electrical Engineering, Physics, Applied Mathematics, Statistics, or a related technical discipline and 4+ years of relevant experience; or a Master's degree plus 2+ years
Strong command of detection and estimation theory, stochastic processes, linear algebra, and statistical signal processing
Demonstrated experience developing radar, RF, or comparable sensor processing algorithms and validating them against real recorded data
Proficiency in MATLAB and Python (NumPy, SciPy) for algorithm development and analysis
Experience with modeling and simulation, including Monte Carlo methods and performance prediction
Ability to derive an approach from first principles when no existing method fits, and to know when an existing method does
Experience guiding or mentoring less experienced technical staff
Strong technical writing and the ability to present complex analysis to technical and non-technical audiences
Ways to Stand Out
Deep experience in one or more of: STAP, adaptive/digital beamforming, SAR/ISAR image formation (back-projection, polar format, autofocus), MTI and clutter cancellation, passive or bistatic radar, or electronic warfare techniques
Experience with cognitive and adaptive radar concepts, including resource management and closed-loop waveform adaptation
Multi-sensor and multi-INT fusion experience
Implementation experience in C/C++ with GPU acceleration (CUDA) or embedded/FPGA targets, including HLS workflows and fixed-point analysis
Experience applying machine learning to RF and radar problems — RF machine learning, learned detection or classification, model-based deep learning and algorithm unrolling, or ML-assisted parameter estimation
Familiarity with digital twin and high-fidelity scene/phenomenology simulation
Experience with field testing, collection planning, and the practical realities of instrumented data collection