At least 7 years of experience developing radar signal-processing algorithms and evaluating them against measured data.
Strong understanding of digital signal processing, radar fundamentals, probability, and statistical estimation.
Experience with FFT-based processing, filtering, constant false alarm rate detection, beamforming, and array processing.
Proficiency in Python or MATLAB for simulation and analysis.
Experience implementing performance-sensitive algorithms in C++ or a comparable language.
Ability to diagnose whether a performance issue originates in an algorithm, hardware, or the test setup.
Experience balancing detection performance with compute, memory, and latency constraints.
Clear technical communication and comfort working across hardware and software teams.
Responsibilities
Develop and implement algorithms for range, Doppler, and angle estimation, detection, and target tracking.
Evaluate waveforms and processing approaches against requirements for range, resolution, coverage, and update rate.
Build simulations to evaluate performance across target characteristics, clutter, interference, and noise.
Develop beamforming, calibration, clutter suppression, and adaptive detection methods.
Analyze recorded radar data to identify missed detections, false alarms, estimation errors, and tracking failures.
Implement and optimize algorithms for real-time operation, working with firmware and software engineers on deployment.
Design bench and field tests that measure detection probability, false alarm rates, estimation accuracy, and track continuity.
Work with RF engineers to understand how antenna performance, channel mismatch, timing, and other hardware effects influence processing.
Build repeatable tools for data analysis, algorithm evaluation, and regression testing.
Document algorithm assumptions, performance results, and tradeoffs so the team can make informed design decisions.
Desired Qualifications
Experience with FMCW radar and MIMO antenna architectures.
Experience detecting and tracking small drones or other targets with low radar cross sections.
Familiarity with micro-Doppler analysis and target classification.
Experience with Kalman filtering, data association, and multi-target tracking.
Experience implementing algorithms on embedded processors, GPUs, or FPGAs.
Experience with outdoor radar testing and challenging clutter environments.
A degree in electrical engineering, applied mathematics, physics, computer science, or a related field.
About Austin Sensing Company
Austin Sensing Company builds radar, acoustic, and RF sensors for defense, public safety, critical infrastructure, and autonomous systems. We design and manufacture our hardware in Austin, Texas, with a focus on making high-performance sensing reliable, affordable, and widely available.
About the Role
We’re hiring a Radar Signal Processing Engineer to develop the algorithms that turn radar measurements into reliable detections and tracks. You’ll work across waveform design, detection, estimation, and tracking, taking algorithms from simulation through implementation and field testing.
You’ll work closely with RF, firmware, and software engineers to understand hardware limitations, improve radar performance, and make algorithms run within real compute and latency constraints. We’re looking for someone who can explain the theory, implement it, and use measured data to determine where it holds up.
What You’ll Do
Develop and implement algorithms for range, Doppler, and angle estimation, detection, and target tracking.
Evaluate waveforms and processing approaches against requirements for range, resolution, coverage, and update rate.
Build simulations to evaluate performance across target characteristics, clutter, interference, and noise.
Develop beamforming, calibration, clutter suppression, and adaptive detection methods.
Analyze recorded radar data to identify missed detections, false alarms, estimation errors, and tracking failures.
Implement and optimize algorithms for real-time operation, working with firmware and software engineers on deployment.
Design bench and field tests that measure detection probability, false alarm rates, estimation accuracy, and track continuity.
Work with RF engineers to understand how antenna performance, channel mismatch, timing, and other hardware effects influence processing.
Build repeatable tools for data analysis, algorithm evaluation, and regression testing.
Document algorithm assumptions, performance results, and tradeoffs so the team can make informed design decisions.
What You’ll Bring
7+ years of experience developing radar signal processing algorithms and evaluating them against measured data.
Strong understanding of digital signal processing, radar fundamentals, probability, and statistical estimation.
Experience with FFT-based processing, filtering, CFAR detection, beamforming, and array processing.
Proficiency in Python or MATLAB for simulation and analysis.
Experience implementing performance-sensitive algorithms in C++ or a comparable language.
The ability to diagnose whether a performance issue comes from an algorithm, the hardware, or the test setup.
Experience balancing detection performance with compute, memory, and latency constraints.
Clear technical communication and comfort working across hardware and software teams.
Preferred Experience
Experience with FMCW radar and MIMO antenna architectures.
Experience detecting and tracking small drones or other targets with low radar cross sections.
Familiarity with micro-Doppler analysis and target classification.
Experience with Kalman filtering, data association, and multi-target tracking.
Experience implementing algorithms on embedded processors, GPUs, or FPGAs.
Experience with outdoor radar testing and challenging clutter environments.
A degree in electrical engineering, applied mathematics, physics, computer science, or a related field.