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Internship Deep Reinforcement Learning Jobs in Reston, VA

EchoStar

Senior AI/ML Architect

Herndon, VA · On-site

$146K - $210K/yr

Familiarity with advanced AI techniques, including deep reinforcement learning, federated learning, and model explainability * Knowledge of AI ethics, regulatory compliance in telecom, and data ...

Staffingine LLC

AI Platform Developer

Herndon, VA · On-site

Machine Learning (ML) & Deep Learning (DL): You'll need a deep understanding of ML concepts (supervised, unsupervised, reinforcement learning) and neural network architectures like CNNs and RNNs.

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How much do internship deep reinforcement learning jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for internship deep reinforcement learning in Reston, VA is $17.72, according to ZipRecruiter salary data. Most workers in this role earn between $15.00 and $20.00 per hour, depending on experience, location, and employer.

What types of projects or tasks can I expect to work on during a deep reinforcement learning internship?

As a Deep Reinforcement Learning (DRL) intern, you'll typically work on projects involving the development, implementation, and evaluation of reinforcement learning algorithms. This might include tasks like training agents in simulated environments, tuning hyperparameters, analyzing performance metrics, and collaborating with team members to integrate DRL solutions into larger systems. You'll also likely spend time reading recent research papers, experimenting with frameworks such as TensorFlow or PyTorch, and presenting your findings to the research team. Collaboration with mentors and other interns is common, and you'll gain hands-on experience that prepares you for more advanced roles in AI research or engineering.

What is an internship in deep reinforcement learning?

An internship in Deep Reinforcement Learning (DRL) is a temporary, hands-on position where interns learn and apply state-of-the-art machine learning algorithms that enable computers to learn decision-making tasks through trial and error. Interns typically work on projects involving neural networks, reward systems, and environments like games or simulations. These internships provide valuable experience with frameworks such as TensorFlow or PyTorch, and exposure to current research in artificial intelligence. The experience helps students or recent graduates build technical skills and prepare for careers in AI research or industry.

What are the key skills and qualifications needed to thrive as an intern in deep reinforcement learning?

To thrive as an Intern in Deep Reinforcement Learning, you need a solid background in mathematics (especially linear algebra, probability, and calculus), programming (Python), and foundational knowledge in machine learning principles, usually supported by ongoing or completed coursework in computer science or related fields. Familiarity with frameworks and tools such as TensorFlow, PyTorch, OpenAI Gym, and experience using version control systems like Git are typically required. Analytical thinking, curiosity, and effective communication are essential soft skills for collaborating on research problems and sharing complex findings. These skills and qualities are crucial for contributing to innovative projects and successfully navigating the challenges of cutting-edge AI research.

What is the difference between Internship Deep Reinforcement Learning vs Data Science Intern?

AspectInternship Deep Reinforcement LearningData Science Intern
Required SkillsMachine learning, programming (Python), reinforcement learning conceptsStatistics, data analysis, programming (Python/R), data visualization
Work EnvironmentResearch labs, AI companies, tech startupsBusiness analytics, tech firms, consulting agencies
Industry UsageAI research, robotics, autonomous systemsBusiness intelligence, marketing, finance

Internship Deep Reinforcement Learning focuses on developing algorithms that enable systems to learn through trial and error, often in AI research or robotics. Data Science Internships involve analyzing data to extract insights and support decision-making. While both roles require programming skills, reinforcement learning emphasizes AI-specific techniques, whereas data science centers on statistical analysis and data visualization.

What job categories do people searching Internship Deep Reinforcement Learning jobs in Reston, VA look for? The top searched job categories for Internship Deep Reinforcement Learning jobs in Reston, VA are:
What cities near Reston, VA are hiring for Internship Deep Reinforcement Learning jobs? Cities near Reston, VA with the most Internship Deep Reinforcement Learning job openings:
Internship Deep Reinforcement Learning jobs near you
Infographic showing various Internship Deep Reinforcement Learning job openings in Reston, VA 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 $36,866 per year, or $17.7 per hour.

Senior Machine Learning Engineer, Public Sector

Scale AI, Inc.

Washington, DC • On-site

Other

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Scale AI rating

8.5

Company rating: 8.5 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

78th of 242 rated software companies

Job description

The goal of a Senior Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and unique access to massive datasets to deliver improvements to our customers.

Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge. Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications.

You will:
  • Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
  • Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
  • Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
  • Work with massive datasets to develop both generic models as well as fine tune models for specific products
  • Build scalable machine learning infrastructure to automate and optimize our ML services
  • Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
  • Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
  • Comfortable with light travel (approximately 10%) for customer interaction and team needs
  • This role will require an active security clearance
Ideally You'd Have:
  • Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
  • Solid background in algorithms, data structures, and object-oriented programming
  • Strong programing skills in Python, experience in Tensorflow or PyTorch
Nice to Haves:
  • Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
  • Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments
  • Experience with computer vision, generative AI models, large language models, or agentic systems
  • Familiarity with ML evaluation frameworks and agentic model design

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

The base salary range for this full-time position in the location of Washington DC is:
$225,750—$282,450 USD

PLEASE NOTE:Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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