1

Internship Applied Scientist Machine Learning Jobs in Washington

We have a career opportunity for a Machine Learning / Data Scientist to develop advanced analytical models and experiments that enhance decision-making, improve forecasting, and uncover insights ...

Distinguished Applied Researcher Overview: At Capital One, we are creating trustworthy and reliable ... Partner with a cross-functional team of data scientists, software engineers, machine learning ...

Required : • MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or a related technical field, or equivalent practical experience. • 5+ years of ...

Showing results 21-40

Internship Applied Scientist Machine Learning information

What types of projects do internship applied scientists in machine learning typically work on, and how do they contribute to the team's goals?

Internship Applied Scientists in Machine Learning often collaborate with multidisciplinary teams to tackle real-world problems using data-driven approaches. Typical projects might include developing and fine-tuning machine learning models, conducting experiments to validate hypotheses, or assisting in the deployment of algorithms into production systems. Interns are expected to contribute fresh perspectives, help with data preprocessing, and perform thorough model evaluations. Through these projects, interns gain hands-on experience while directly supporting the team's research and product development objectives.

What is the difference between Internship Applied Scientist Machine Learning vs Internship Data Scientist?

AspectInternship Applied Scientist Machine LearningInternship Data Scientist
Required CredentialsRelevant degrees in Computer Science, Data Science, or related fields; knowledge of ML frameworksDegrees in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentResearch and development teams, focus on ML model developmentBusiness teams, focus on data analysis and insights
Employer & Industry UsageTech companies, AI-focused organizationsVarious industries including tech, finance, healthcare
Comparison Search IntentUnderstanding roles in ML research and developmentUnderstanding data analysis and business insights roles

Internship Applied Scientist Machine Learning roles focus on developing and applying machine learning models, often in research settings. In contrast, Internship Data Scientist positions emphasize analyzing data to generate insights for business decisions. Both roles require strong analytical skills and relevant educational backgrounds, but they differ in their primary focus and work environment.

What are the key skills and qualifications needed to thrive as an internship applied scientist in machine learning, and why are they important?

To thrive as an Internship Applied Scientist in Machine Learning, you need a solid background in mathematics, statistics, and computer science, often supported by coursework or research experience in machine learning and data analysis. Familiarity with tools such as Python, TensorFlow, PyTorch, and experience working with large datasets are highly valued, along with knowledge of version control systems like Git. Strong problem-solving skills, curiosity, and the ability to communicate complex concepts clearly set top candidates apart. These competencies are crucial for effectively designing, implementing, and presenting machine learning solutions that address real-world challenges.

What does an internship applied scientist in machine learning do?

An Internship Applied Scientist in Machine Learning works on real-world projects involving the design, development, and evaluation of machine learning models and algorithms. Their responsibilities typically include data analysis, building predictive models, experimenting with new techniques, and collaborating with engineers and researchers to solve complex problems. Interns gain hands-on experience with tools like Python, TensorFlow, or PyTorch, and contribute to advancing the company's AI capabilities. The role requires a strong foundation in mathematics, statistics, and computer science, as well as the ability to communicate findings to both technical and non-technical stakeholders.
What are the most commonly searched types of Applied Scientist Machine Learning jobs in Washington? The most popular types of Applied Scientist Machine Learning jobs in Washington are:
What are popular job titles related to Internship Applied Scientist Machine Learning jobs in Washington? For Internship Applied Scientist Machine Learning jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Internship Applied Scientist Machine Learning jobs in Washington look for? The top searched job categories for Internship Applied Scientist Machine Learning jobs in Washington are:
Infographic showing various Internship Applied Scientist Machine Learning job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Research Scientist - RF Machine Learning

Peraton

College Park, MD • On-site

Full-time

Re-posted 27 days ago


Peraton rating

8.3

Company rating: 8.3 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

47th of 221 rated it services


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

#PLABS26

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

What Peraton employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Peraton logo

About Peraton

Sourced by ZipRecruiter

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