Signal Processing Engineer / Developer

Job Description

Location: Atlanta, GA (Hybrid preferred)

Clearance: Must be authorized to work in the U.S. (U.S. Citizenship or Permanent Residency strongly preferred)

Employment Type: Full-time

About Us

We are a small, agile, and highly experienced R&D company with over 25 years of success delivering cutting-edge algorithmic and software solutions to U.S. government and commercial partners. Our work combines deep scientific understanding with innovative engineering across domains such as machine learning, physics-based modeling, modeling & simulation, and signal processing.

Our Advanced Signal Processing Group develops technologies that extract critical insights from complex sensor data—spanning radar, RF, acoustic, and other modalities—to support applications in defense, aerospace, surveillance, and more.

Position Summary

We are seeking a Signal Processing Engineer or Developer who is passionate about algorithm development, data-driven modeling, and real-time or near-real-time signal analysis. This role involves research, prototyping, and deployment of signal processing systems that directly support national security and mission-critical applications.

You'll join a multidisciplinary technical team and contribute to designing, implementing, and optimizing algorithms that process noisy, sparse, or high-volume signals from challenging environments.

Key Responsibilities

Design and implement signal processing algorithms for real-world sensing and detection problems.

Work with a variety of signal modalities including RF, acoustic, radar, and EO/IR systems.

Translate mathematical models and physical principles into software implementations (e.g., Python, C++).

Optimize code for performance, accuracy, and robustness in resource-constrained environments.

Contribute to data collection, signal characterization, and analysis pipelines.

Collaborate in R&D proposal writing, internal reviews, and technical briefings to customers.

Support the integration of algorithms into prototype or operational systems.

Required Qualifications

Education: BS, MS, or PhD in Electrical Engineering, Computer Engineering, Applied Physics, or related field.

Strong foundation in:

Digital Signal Processing (DSP)

Fourier analysis, filtering, time-frequency representations

Detection theory, estimation, noise modeling

Proficiency in at least two of the following:

Python (NumPy/SciPy/SciKit)

C/C++ for embedded or performance-critical systems

Signal processing frameworks or data visualization tools

Excellent communication skills, ability to document and present technical work clearly

Preferred Qualifications

Experience with sensor systems: radar, sonar, RF, or other sensing modalities

Familiarity with machine learning integration into signal processing workflows

Knowledge of software-defined radio (e.g., GNURadio, USRP, etc.)

Background in working with DoD programs, SBIR/STTRs, or applied defense R&D

Experience in simulation environments or physics-based modeling tools

Why Join Us

Opportunity to contribute to mission-critical, high-impact projects

Work with a small team of experts in a collaborative and innovative environment

Exposure to cross-domain technologies including AI/ML and physics-based models

Competitive salary and benefits, with flexible work arrangementsCompany Description

We are an award-winning engineering firm with over 20 years of history as a comprehensive product and service provider in the areas of Predictive Analytics, Modeling and Simulation, Data Science, and Failure Analysis for analyzing and predicting the health of critical assets. Operating at the intersection of data science modeling and simulation and engineering, we develop sophisticated algorithms for government intelligence applications.

The company has built a solid reputation as a leading solution provider for innovative software and hardware products. We support all branches of the military and various commercial sectors by monitoring their complex assets and delivering advanced analytical capabilities that enable informed decision-making and enhanced operational readiness.

Full-time