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$53.5K

$131.3K

$193.5K

How much do signal processing machine learning jobs pay per year?

As of Jun 10, 2026, the average yearly pay for signal processing machine learning in the United States is $131,349.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,500.00 and $147,500.00 per year, depending on experience, location, and employer.

What are some typical projects or responsibilities for a Signal Processing Machine Learning professional?

As a Signal Processing Machine Learning professional, you can expect to work on projects that involve developing and optimizing algorithms for tasks such as audio or image recognition, anomaly detection, or sensor data analysis. Daily responsibilities often include pre-processing and cleaning large datasets, feature extraction, building and training machine learning models, and validating system performance. Collaboration with cross-functional teams—such as hardware engineers, data scientists, and software developers—is common to integrate your solutions into products or services. The work environment is typically dynamic and may involve both research-oriented tasks and practical implementation to create impactful, data-driven applications.

What is a Signal Processing Machine Learning job?

A Signal Processing Machine Learning job involves developing algorithms that analyze and process signals (such as audio, images, video, or sensor data) using machine learning techniques. Professionals in this role apply concepts from digital signal processing (DSP) to extract meaningful patterns, enhance signal quality, and improve data-driven predictions. They work in diverse fields like telecommunications, biomedical engineering, finance, and autonomous systems. Typical tasks include feature extraction, noise reduction, and deploying deep learning models for real-time signal interpretation. Strong skills in mathematics, programming (Python, MATLAB), and frameworks like TensorFlow or PyTorch are essential.

What are the key skills and qualifications needed to thrive in the Signal Processing Machine Learning position, and why are they important?

To thrive in Signal Processing Machine Learning, you need a strong background in mathematics, digital signal processing, and machine learning, generally supported by a relevant degree in electrical engineering, computer science, or a related field. Experience with programming languages such as Python or MATLAB, familiarity with frameworks like TensorFlow or PyTorch, and knowledge of signal processing libraries are typically required. Analytical thinking, problem-solving ability, and effective communication are crucial soft skills in this position. These competencies enable you to design, implement, and refine advanced algorithms that address complex, real-world data challenges.

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Signal Processing Machine Learning jobs near you
LEAD ENGINEER - SR. RESEARCH ENGINEER - Signal Processing Engineer

LEAD ENGINEER - SR. RESEARCH ENGINEER - Signal Processing Engineer

Southwest Research Institute - Fulltime

San Antonio, TX • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Southwest Research Institute rating

8.8

Company rating: 8.8 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

6th of 57 rated research

Job description

Who We Are: Ongoing threats to national security require timely intelligence data, including signal intelligence obtained through electronic surveillance. Since the 1940s, SwRI has supported U.S. and friendly foreign governments, as well as commercial clients.

While a non-profit research institution, SwRI develops state of the art solutions to real problems. Objectives of this Role: Work with multidisciplinary team of engineers, software developers, and technicians in the execution of R&D, design, and testing systems and software in support of national security. Design, develop, integrate, test and deploy new signal processing capabilities in the areas of energy detection, channelization, signal recognition, signal demodulation/decoding & encoding/modulating, RF geolocation and electronic warfare.

Simulate and develop radar signal processing algorithms for blind radar detection and parameterization in a complex propagation and environment (HF ionospheric propagation channels). Simulate HF propagation using advanced tools for predicting signal effects due to multi-path and scattering to evaluate algorithm performance with realistic data. Daily and Monthly Responsibilities: Collaborate with client technical representatives and SwRI senior engineering and software staff to develop algorithms and write software and scripts for signal processing applications and to test software and related systems.

Work at SwRI laboratories and support short-term travel to government facilities/military bases or other customer facilities for system installations and to provide technical support within and outside the United States. Present progress and findings to your project teams and clients. Prepare technical documents and support proposal preparation as required.

Requirements: Requires a Masters or a PhD in Electrical Engineering, Electrical and Computer Engineering or Computer Engineering. 3-7 years: Applicants with PhD qualify with 3 years and those with a Masters qualify with 7 years work experience in signal processing with understanding of radar system concepts and waveforms. Experience with C/C++ and Python are required.

Over-the-horizon radar (OTHR) or ionospheric sounder processing experience desired. Communications signal processing desired. Linux and MATLAB proficiency are desired.

Coursework and/or research experience with application of machine learning to signal processing is strongly desired. A valid/clear driver's license is required.

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