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Senior Machine Learning Scientist Jobs in Washington

Parsons

Machine Learning / Data Scientist

Washington, DC · On-site

$88K - $154K/yr

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 ...

Capital One

Sr. Lead Machine Learning Engineer

Mclean, VA · On-site +1

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar ...

Capital One

Sr. Lead Machine Learning Engineer

Mclean, VA · On-site +1

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE), you'll be part ... Master's or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar ...

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Senior Machine Learning Scientist information

See Washington salary details

$75.3K

$125.2K

$186.3K

How much do senior machine learning scientist jobs pay per year?

As of Aug 10, 2026, the average yearly pay for senior machine learning scientist in Washington is $125,202.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,600.00 and $141,600.00 per year, depending on experience, location, and employer.

What is the difference between Senior Machine Learning Scientist vs Data Scientist?

AspectSenior Machine Learning ScientistData Scientist
CredentialsMaster's or PhD in CS, ML, or related fieldBachelor's or Master's in CS, Statistics, or related field
Work EnvironmentFocus on developing ML models, algorithms, and researchData analysis, visualization, and business insights
Industry UsageUsed in AI-driven companies, tech firms, research labsCommon across industries for data analysis and reporting

While both roles involve working with data, Senior Machine Learning Scientists focus on developing advanced ML models and algorithms, often requiring research and deep technical expertise. Data Scientists typically analyze data to generate insights and support decision-making. The roles overlap but differ mainly in technical depth and focus area.

What is a senior machine learning scientist?

Senior Machine Learning Scientists are experienced professionals who design, develop, and implement advanced machine learning models to solve complex business or research problems. They are responsible for leading projects, mentoring junior team members, and staying updated on the latest AI and data science technologies. Their work often involves analyzing large datasets, selecting the right algorithms, and optimizing model performance for real-world applications. In addition to technical expertise, they often collaborate cross-functionally to align machine learning solutions with organizational goals.

What are the key skills and qualifications needed to thrive as a senior machine learning scientist?

To thrive as a Senior Machine Learning Scientist, you need expertise in machine learning algorithms, statistical analysis, programming (usually in Python or R), and an advanced degree (often a Ph.D.) in a quantitative field. Experience with tools such as TensorFlow, PyTorch, scikit-learn, cloud platforms, and version control systems is typically expected, along with knowledge of deploying models in production environments. Exceptional problem-solving, communication, and leadership skills help you translate complex data insights into actionable business solutions and mentor junior team members. These skills are crucial for developing innovative models, ensuring robust deployment, and driving impactful data-driven decisions.

What are some common challenges senior machine learning scientists face when deploying models to production environments?

Senior Machine Learning Scientists often encounter challenges such as ensuring model scalability, maintaining model performance over time, and addressing data drift once models are deployed to production. Collaborating closely with engineering and operations teams is crucial to streamline deployment pipelines and monitor models for real-world reliability. It’s also important to communicate findings and potential risks to stakeholders, and to regularly update models based on new data or business requirements. These aspects make strong cross-functional teamwork and problem-solving skills essential in this role.
What are the most commonly searched types of Machine Learning Scientist jobs in Washington? The most popular types of Machine Learning Scientist jobs in Washington are:
What are popular job titles related to Senior Machine Learning Scientist jobs in Washington? For Senior Machine Learning Scientist jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Scientist jobs in Washington look for? The top searched job categories for Senior Machine Learning Scientist jobs in Washington are:
What cities in Washington are hiring for Senior Machine Learning Scientist jobs? Cities in Washington with the most Senior Machine Learning Scientist job openings:
Senior Machine Learning Scientist jobs near you
Infographic showing various Senior Machine Learning Scientist job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $125,202 per year, or $60.2 per hour.

Research Scientist - RF Machine Learning

Peraton

College Park, MD • On-site

$135K - $216K/yr

Full-time

Re-posted 2 days ago

Peraton rating

8.3

Company rating: 8.3 out of 10

Based on 56 frontline employees who took The Breakroom Quiz

50th of 223 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.
EEO
EEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.

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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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