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Research Machine Learning Federated Learning Jobs in Maryland

PassFort

Machine Learning Engineer

Berlin, MD · On-site

$79.93 - $137.02/hr

Combine cutting-edge robotics research in end-to-end learning & Vision Language Action Model with ... Heavy machinery, light years ahead. sensmore automates the world's largest machines with ...

Varsity Tutors

Machine Learning Tutor

Bowie, MD · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

Varsity Tutors

Machine Learning Tutor

Laurel, MD · Remote

$18 - $40/hr

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ...

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Research Machine Learning Federated Learning information

What is a researcher in machine learning federated learning?

A Researcher in Machine Learning Federated Learning is a professional who investigates and develops methods to train machine learning models across multiple decentralized devices or servers, while keeping data localized and private. Their work focuses on improving algorithms, ensuring data privacy, and addressing challenges related to distributed learning, communication efficiency, and model accuracy. They often collaborate with other researchers, publish findings, and contribute to advancing technologies that make it possible to use sensitive data for AI without compromising privacy.

What are the key skills and qualifications needed to thrive as a researcher in machine learning federated learning?

To thrive as a Researcher in Machine Learning Federated Learning, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant advanced degree (e.g., PhD or MSc). Familiarity with Python, TensorFlow, PyTorch, and distributed computing frameworks, as well as knowledge of privacy-preserving techniques and relevant research publications, is essential. Excellent analytical thinking, problem-solving abilities, and clear scientific communication are key soft skills for success in collaborative research environments. These competencies are vital to drive innovation, rigorously evaluate federated learning approaches, and advance privacy-preserving AI technologies.

What are some common challenges faced when implementing federated learning in a research environment?

One of the primary challenges in research-focused federated learning roles is ensuring data privacy and security while maintaining model performance across distributed devices. Researchers must also address issues such as handling heterogeneous data sources, communication bottlenecks between nodes, and the complexity of debugging decentralized systems. Collaborating with cross-functional teams—such as data engineers, privacy experts, and domain specialists—is vital to overcome these hurdles and drive successful outcomes. Staying updated with the latest advancements and actively contributing to open-source initiatives can also help researchers address these evolving challenges.

What is the difference between Research Machine Learning Federated Learning vs Data Scientist?

AspectResearch Machine Learning Federated LearningData Scientist
CredentialsAdvanced degrees in CS, ML, or related fields; research experienceBachelor's or Master's in Data Science, Statistics, or related fields
Work EnvironmentResearch labs, academic institutions, tech companies focusing on privacy-preserving MLBusiness environments, analytics teams, data-driven departments
Industry UsageDeveloping federated algorithms, privacy-preserving ML modelsData analysis, modeling, reporting, and insights generation

Research Machine Learning Federated Learning specialists focus on developing privacy-preserving algorithms across distributed data sources, often in research or R&D settings. Data Scientists analyze and interpret data to inform business decisions. While both roles require strong ML knowledge, federated learning roles emphasize distributed systems and privacy, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Research Machine Learning Federated Learning jobs in Maryland?

For Research Machine Learning Federated Learning jobs in Maryland, the most frequently searched job titles are:

What job categories do people searching Research Machine Learning Federated Learning jobs in Maryland look for?

The top searched job categories for Research Machine Learning Federated Learning jobs in Maryland are:

What cities in Maryland are hiring for Research Machine Learning Federated Learning jobs?

Cities in Maryland with the most Research Machine Learning Federated Learning job openings:

Research Machine Learning Federated Learning jobs near you

Research Scientist - RF Machine Learning

College Park, MD • On-site

Peraton
IT Services • 10K+ employees

8.3

Company rating: 8.3 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

51st of 225 rated it services

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Full-time

Re-posted 18 days ago

Job description

Responsibilities

Peraton Labs is seeking a poly cleared Senior Research Scientist to support cleared research and development efforts for a Maryland-based IC customer. This role will focus on leading the design, development, prototyping, and evaluation of RF Machine Learning algorithms and signal processing techniques for advanced wireless, spectrum, cyber, and communications research.

You'll work on mission-focused R&D efforts that move from research concepts to working prototypes and operationally relevant capabilities. You will collaborate with researchers, software engineers, signal processing experts, and customer stakeholders to solve complex problems involving RF sensing, signal characterization, waveform analysis, spectrum awareness, and machine learning-enabled wireless systems.

This position requires full-time on-site work at a customer site near College Park, MD.

Key responsibilities may include

  • Lead the design, development, prototyping, and evaluation of RF/ML algorithms for wireless, spectrum, and communications applications
  • Research and implement machine learning approaches for RF signal detection, classification, characterization, anomaly detection, emitter identification, spectrum sensing, or waveform analysis
  • Develop and evaluate algorithms using modern machine learning frameworks such as PyTorch, TensorFlow, Keras, scikit-learn, JAX, or similar tools
  • Apply strong digital signal processing and RF domain knowledge to develop, train, test, and validate models against real-world or simulated RF data
  • Design data collection, labeling, preprocessing, feature extraction, training, evaluation, and experimentation workflows for RFML research
  • Develop software prototypes using Python, C/C++, MATLAB, GNU Radio, or similar tools
  • Analyze RF signals, wireless protocol behavior, modulation characteristics, channel effects, interference, noise, and system performance
  • Work with RF datasets, signal captures, IQ data, SDR platforms, and lab or field-collected spectrum data
  • Support integration of RFML capabilities into larger research prototypes, testbeds, cyber experimentation platforms, or operationally relevant systems
  • Communicate research findings, technical approaches, experiment results, and prototype capabilities through customer briefings, technical reports, whitepapers, and publications
  • Provide technical leadership, mentor junior researchers or engineers, and help shape future RFML research direction

*This position may be eligible for an increased sign-on bonus. Eligibility, bonus amount, and applicable terms and conditions will be discussed during the recruiting process*

#MDFSP

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Qualifications

Minimum Qualifications

  • Minimum of 6+ years of experience with a Bachelor's degree, 4+ years of experience with a Master's degree, or 2+ years of experience with a Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related discipline. In lieu of a Bachelors, an additional 4 years of experience is required for a total of 10+ years.
  • Strong background in Radio frequency Machine Learning, digital signal processing, wireless communications, or RF systems research
  • Experience designing, developing, training, testing, or evaluating machine learning models for RF, wireless, spectrum, signal processing, or communications applications
  • Experience with modern machine learning frameworks such as PyTorch, TensorFlow, Keras, scikit-learn, or similar tools
  • Strong Experience programming in Python and at least one additional language such as C/C++, Java, or similar
  • Experience working with RF data, signal captures, IQ samples, simulated waveforms, or real-world wireless datasets
  • Experience working in Linux-based dev environments
  • Ability to develop, test, troubleshoot, document, and demonstrate research prototypes
  • Strong written and verbal communication skills, including the ability to present technical concepts and research results to technical stakeholders
  • US Citizenship is a requirement for this position
  • This position requires an active/current TS/SCI w/ Polygraph

Desired Additional Qualifications

  • Advanced degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related technical field is preferred
  • Demonstrated history of research in Machine Learning and RF spectrum domains, including publications, prototypes, proposals, patents, technical reports, or customer-facing research briefings
  • Experience with RFML applications such as signal classification, modulation recognition, emitter identification, spectrum sensing, anomaly detection, interference detection, protocol inference, or RF fingerprinting
  • Experience with SDR platforms such as Ettus USRP, HackRF, BladeRF, LimeSDR, or similar hardware
  • Familiarity with SDR software and RF development tools such as GNU Radio, UHD/USRP, MATLAB, Simulink or similar tools
  • Experience with wireless systems or protocols such as LTE, 5G, Wi-Fi, SATCOM, MANET, tactical radio systems, mesh networks, or custom waveform environments
  • Experience with RF test equipment such as spectrum analyzers, signal generators, oscilloscopes, vector signal analyzers, channel emulators, or RF front-end equipment
  • Experience with deep learning approaches for signal processing, including CNNs, RNNs, transformers, autoencoders, contrastive learning, self-supervised learning, or generative models
  • Experience with data engineering for RFML, including dataset generation, augmentation, labeling, synthetic data, simulation, model evaluation, and experiment tracking
  • Experience with tools such as NumPy, SciPy, Pandas, cuSignal, CUDA, MLflow, Weights & Biases, DVC, or similar tools
  • Experience integration ML models into deployable prototypes, edge systems, containers, testbeds, or cyber/radio experimentation environments
  • Experience with RF cyber research, wireless security, electronic warfare, spectrum operations, protocol reverse engineering, or adversarial ML
  • Ability to serve as a technical lead, task lead, or principal investigator on DoD/IC research efforts
Peraton Overview

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can't be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we're keeping people around the world safe and secure.

Target Salary Range$135,000 - $216,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual's experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.EEOEEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.Employment Type: FULL_TIME
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About Peraton

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At Peraton, we re at the forefront of delivering the next big thing every day. We re the partner of choice to help solve some of the world s most daunting challenges, delivering bold, new solutions to keep people around the world safer and more secure.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Herndon, VA, US

Year founded

2017

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