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Reinforcement Learning Engineer Jobs in Washington

Cymertek

Machine Learning Engineer

Chantilly, VA · On-site

Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ... Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning ...

Cymertek Corporation

Machine Learning Engineer

Reston, VA · On-site

$110 - $170/hr

Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ... Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning ...

Cymertek

Machine Learning Engineer

Tysons, VA · On-site

Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ... Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning ...

Cymertek

Machine Learning Engineer

Reston, VA · On-site

Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement ... Proficiency in programming languages (e.g., Python, R, Java) * Experience with machine learning ...

Bright Vision Technologies

Applied RL Engineer

Reston, VA · On-site

$100 - $150/hr

Job Summary We are looking for a Reinforcement Learning Engineer to design, train, and deploy RL-based systems for high-impact decision-making problems where supervised learning alone is insufficient.

TheIncLab

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Supervised, unsupervised, and reinforcement learning * Neural networks, decision trees, ensemble ... Feature engineering and preprocessing * Data augmentation strategies for training robustness

TheIncLab

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Supervised, unsupervised, and reinforcement learning * Neural networks, decision trees, ensemble ... Feature engineering and preprocessing * Data augmentation strategies for training robustness

TheIncLab

Senior Machine Learning Engineer

Mclean, VA · On-site

$105K - $145K/yr

Supervised, unsupervised, and reinforcement learning * Neural networks, decision trees, ensemble ... Feature engineering and preprocessing * Data augmentation strategies for training robustness

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Reinforcement Learning Engineer information

See Washington salary details

$43K

$131.2K

$216.9K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for reinforcement learning engineer in Washington is $131,228.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,000.00 and $171,600.00 per year, depending on experience, location, and employer.

What is a reinforcement learning engineer?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are some common challenges faced by reinforcement learning engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

What are the key skills and qualifications needed to thrive as a reinforcement learning engineer, and why are they important?

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

What is the difference between Reinforcement Learning Engineer vs Machine Learning Engineer?

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What are popular job titles related to Reinforcement Learning Engineer jobs in Washington?

For Reinforcement Learning Engineer jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Reinforcement Learning Engineer jobs in Washington look for?

The top searched job categories for Reinforcement Learning Engineer jobs in Washington are:

What cities in Washington are hiring for Reinforcement Learning Engineer jobs?

Cities in Washington with the most Reinforcement Learning Engineer job openings:

Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Washington as of August 2026, with employment types broken down into 88% Full Time, and 12% Contract. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $131,228 per year, or $63.1 per hour.

Senior Data Scientist / Machine Learning Engineer with Security Clearance

Waypoint Human Capital

Tysons, VA • On-site

Other

Re-posted 8 days ago

Job description

Waypoint Human Capital Senior Data Scientist / Machine Learning Engineer * Tysons, VA Position Title: Senior Data Scientist / Machine Learning Engineer Position Type: Full-Time, On-Site Position Location: Tysons, VA Clearance Required: Active TS/SCI with CI Polygraph or Full Scope Polygraph Waypoint's client is seeking a dynamic Senior Data Scientist / Machine Learning Engineer with an active TS/SCI CI Poly or higher to join their team. The Senior Data Scientist / Machine Learning Engineer will work directly with data scientists, software engineers, and subject matter experts in the definition of new analytics capabilities able to provide federal customers with the information they need to make proper decisions and enable their digital transformation. This position works directly with data scientists, software engineers, and subject matter experts to research, design, and deploy machine learning algorithms that support federal customers in digital transformation and data-driven decision making. They will contribute to new analytics capabilities and assist customers in building their own applications. This position requires a bachelor's degree in Computer Science, Electrical Engineering, Statistics, or a related field, 5 to 10 years of relevant experience, and strong Python and applied ML skills. An active TS/SCI with CI Polygraph or Full Scope Polygraph is required. Responsibilities The responsibilities include, but are not limited to: * Research, design, implement, and deploy Machine Learning algorithms for enterprise applications. * Assist and enable federal customers to build their own applications. * Contribute to the design and implementation of new features. Required * Active Top Secret clearance with CI Polygraph or Full Scope Polygraph. * Bachelor's degree in Computer Science, Electrical Engineering, Statistics, or equivalent fields required. * MS or PhD in Computer Science, Electrical Engineering, Statistics, or equivalent fields preferred. * Minimum 5–10 years relevant work experience preferred. * Excellent programming skills in Python. * Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning). * Strong mathematical background (linear algebra, calculus, probability, and statistics). * Experience with scalable Machine Learning (MapReduce, streaming). * Ability to drive a project and work both independently and in a team. * Smart, motivated, can-do attitude, and seeks to make a difference. * Excellent verbal and written communication skills. * Passion for developing team-oriented solutions to complex engineering problems. * Thrive in an autonomous, empowering, and exciting environment. * Ability to collaborate across multiple functional teams to improve scalability. * Ability to convey highly technical concepts and information in written form to both technical and non-technical audiences. * Ability to work on multiple concurrent projects. * Strong self-motivation and the ability to work with minimal supervision. * Team-oriented, energetic, results- and delivery-focused, with a strong commitment to quality and meeting deadlines. * Ability to work in an Agile environment. Desired * Hands-on experience deploying and operating applications using IaaS and PaaS on major cloud providers, including Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP). * Proficient in leveraging modern LLM tools to accelerate development workflows and enhance code quality. * Experience with deep learning. * Experience with natural language processing (NLP). * Experience with computer vision. * Experience with reinforcement learning. Apply Now
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