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Remote Signal Processing Jobs in Washington, DC (NOW HIRING)

Astrion

Surveillance Radar Engineer

Washington, DC · Remote

$120K - $140K/yr

Remote JOB STATUS: Full-time CLEARANCE: BI investigation CERTIFICATION: N/A TRAVEL: as needed Must be US citizen Astrion is seeking a Surveillance Radar Engineer to provide technical subject matter ...

GRVTY

Senior Scientist

Herndon, VA · On-site +1

$94K - $128K/yr

Conduct multi-platform remote sensing analytics across varied sensors, collection geometries, and ... Experience with image processing and digital signal processing tools for short-wave and mid-wave ...

Spear AI

Machine Learning Engineer

Washington, DC · On-site +1

Work with signal processing data and time-series analysis * Improve local development and CI/CD for ... Onsite / Remote / Flexible work arrangements or hybrid options (position dependent) * Relocation ...

Signal Vine, Inc

Account Manager (REMOTE)

Alexandria, VA · On-site +1

Company Description Signal Vine is in search of a professional Account Manager with a competitive ... Additionally, during our interview process, our goal will be to learn more about you and yours will ...

GRVTY

Senior Scientist

Herndon, VA · On-site +1

$150K - $235K/yr

Conduct multi-platform remote sensing analytics across varied sensors, collection geometries, and ... Experience with image processing and digital signal processing tools for short-wave and mid-wave ...

iDirect GOVERNMENT

Senior FPGA Engineer

Herndon, VA · On-site +1

$91K - $159K/yr

This position is based out of our Herndon, VA location with the option of a remote work schedule ... Experience in Digital Signal Processing on FPGAs and SDR waveform implementation * Experience in ...

Expression

AI/ML Engineer

Washington, DC · On-site +1

$130K - $170K/yr

Experience applying AI to sensor analytics, time-series data, or signal processing. * Experience ... Hybrid or Remote with limited travel Benefits: Expression offers competitive salaries and benefits ...

GRVTY

Software Engineer, Senior

Herndon, VA · On-site +1

$126K - $166K/yr

Background in signal processing, image processing, or remote sensing data workflows. * Experience with simulation, modeling, or mission analysis software in a defense or intelligence context.

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Showing results 21-40

All JobsSignal Processing JobsRemote Signal Processing JobsRemote Signal Processing Jobs in Washington, DC

Remote Signal Processing information

See Washington, DC salary details

$60.6K

$148.8K

$219.2K

How much do remote signal processing jobs pay per year?

As of Aug 8, 2026, the average yearly pay for remote signal processing in Washington, DC is $148,765.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,900.00 and $167,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a remote signal processing engineer?

To thrive as a Remote Signal Processing Engineer, you need a strong background in electrical engineering, mathematics, and digital signal processing (DSP), usually backed by a relevant degree. Familiarity with software tools such as MATLAB, Python, and DSP libraries, as well as knowledge of remote communication protocols, is typically required. Excellent problem-solving abilities, independent work ethic, and effective remote communication skills help set top performers apart. These skills ensure accurate data analysis, efficient collaboration, and the successful development and deployment of signal processing solutions in distributed work environments.

What is remote signal processing?

Remote signal processing involves analyzing and interpreting signals, such as audio, video, or sensor data, from a distance using digital tools and algorithms. Professionals in this field work remotely to develop and implement software solutions that process various types of signals for applications like telecommunications, medical imaging, and radar systems. This job typically requires expertise in signal processing theory, programming, and sometimes machine learning, all of which can be done from a remote location using specialized software and collaborative tools.

What are some common challenges faced by professionals working in remote signal processing roles, and how can they be addressed?

One common challenge in remote signal processing roles is ensuring reliable data transmission and synchronization when working with distributed or cloud-based systems. Professionals often need to address latency, bandwidth limitations, and data integrity issues, especially when collaborating with geographically dispersed teams. Effective communication, robust data validation protocols, and leveraging version control tools can help mitigate these challenges. Additionally, staying updated with the latest remote collaboration technologies and workflow management tools can streamline project progress and enhance team productivity.
What are the most commonly searched types of Signal Processing jobs in Washington, DC? The most popular types of Signal Processing jobs in Washington, DC are:
What are popular job titles related to Remote Signal Processing jobs in Washington, DC? For Remote Signal Processing jobs in Washington, DC, the most frequently searched job titles are:
What job categories do people searching Remote Signal Processing jobs in Washington, DC look for? The top searched job categories for Remote Signal Processing jobs in Washington, DC are:
Remote Signal Processing jobs near you
Infographic showing various Remote Signal Processing job openings in Washington, DC as of August 2026, with employment types broken down into 87% Full Time, 10% Part Time, and 3% Contract. Highlights an 100% Remote job distribution, with an average salary of $148,765 per year, or $71.5 per hour.

Principal Scientist - AI/ML Specialization - WFH1651

Global InfoTek, Inc.

Reston, VA • On-site, Remote

Full-time

Re-posted 17 days ago

Job description

Clearance Level:
US Citizenship: Required
Job Classification: Full Time
Location: Remote
Years of Experience: 10+ years of relevant experience
Education Level: Advanced degree (MS or PhD) in Electrical Engineering, Computer Science, Applied Mathematics, or a closely related quantitative field. Experience may be considered in place of education requirement.
Briefly Describe the Work:
GITI is seeking a Principal Scientist to serve as the senior technical authority on an R&D program focused on passive RF emitter identification and network analysis from real-time sensor data streams. The Principal Scientist leads independent, hands-on analysis of NDF (Network Description File) sensor datasets, provides technical direction across parallel research threads, and serves as the primary technical advisor to the government sponsor. The role spans the full research lifecycle: formulating hypotheses, writing and executing analytical code in Python and Jupyter notebooks, interpreting and validating results, and communicating findings to both technical peers and non-specialist stakeholders. This is a deeply technical, hands-on position - the Principal Scientist conducts analysis directly and does not delegate technical work as a substitute for personal proficiency. The candidate will work within a small, distributed team operating in air-gapped Linux environments on resource-constrained tactical edge hardware, with no cloud computing.
Responsibilities:
  • Conduct independent, hands-on data analysis on RF sensor datasets using Python and Jupyter notebooks - formulating hypotheses, writing and running analytical code, interpreting results, and producing findings that directly advance program research objectives
  • Provide technical advice and research direction across a multidisciplinary team; define analytical objectives, review and validate technical outputs from AI/ML engineers and software developers, and ensure coherence across parallel research threads
  • Serve as primary technical advisor to the government sponsor: translate operational requirements into research objectives, communicate findings clearly to non-specialist stakeholders, and maintain program alignment with sponsor priorities through written reports and technical presentations
  • Design and execute analytical investigations into RF sensor data quality, emitter behavior, and attribution reliability - including characterizing error sources, identifying systematic artifacts, and developing methods to distinguish real physical signatures from sensor or processing artifacts
  • Produce technical documentation - working notes, research findings, monthly status reports, and briefing materials - that accurately represent the scope and confidence level of analytical results

Expert-level career professional recognized as a technical authority in RF systems, signals intelligence, or a closely related applied domain. Exercises broad independent judgment in defining research approach, evaluating methods, and interpreting results. Operates with minimal supervision; accountable for the scientific integrity and practical relevance of program research outputs. Advanced degree (MS or PhD) with 10+ years of hands-on applied R&D experience.
Required Skills:
  • 10+ years of hands-on applied R&D experience in RF systems, signals intelligence, electronic warfare, or related domains.
  • Proven ability to quickly acquire domain knowledge; specifically in the areas of wireless digital communications and military techniques, tactics, and procedures
  • Demonstrated ability to independently develop and execute data analyses in Python or equivalent tools on real sensor datasets; must be capable of writing production-quality analytical code, not merely directing others to do so
  • Experience addressing common problems with large quantities of real-world data, such as imputation, noise, bias, and errors
  • Track record of working effectively on constrained-hardware edge systems - no cloud, no discrete GPU - with attention to computational efficiency and multi-core, multi-thread performance on x86 platforms

Desired Skills:
  • Deep familiarity with RF signal characteristics, sensor phenomenology, and the interpretation of passive receiver data - including recognition of processing artifacts, attribution ambiguities, and the limits of sensor-derived measurements
  • Hands-on experience applying machine learning - particularly metric learning, deep learning networks, or similarity-learning architectures - to RF or time-series signal data, including feature engineering, training pipeline development, and model validation
  • Familiarity with TDMA network protocols, emitter identification techniques (CID/PID), and the signal processing challenges of dense, contested electromagnetic environments
  • Experience with interferometric direction-finding, TDOA geolocation, or related passive geolocation methods, including practical knowledge of their failure modes and accuracy limitations
  • Experience with binary serialization formats (FlatBuffers, Protocol Buffers) and high-throughput sensor data pipelines operating in near-real-time on resource-constrained hardware
  • Background in statistical signal processing - error ellipses, bearing estimation uncertainty, feature reliability under noise - with the ability to distinguish statistically significant findings from artifacts of small sample size or improper normalization

Relevant Certifications:
  • Professional certifications in data science, signal processing, or related technical fields. Advanced academic credentials (PhD, MS) in a relevant quantitative discipline are strongly preferred and may substitute for certifications.

Global InfoTek, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability.
About Global InfoTek, Inc. Global InfoTek Inc. has an award-winning track record of designing, developing, and deploying best-of-breed technologies that address the nation's pressing cyber and advanced technology needs. GITI has rapidly merged pioneering technologies, operational effectiveness, and best business practices for over two decades.

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