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Internship Deep Reinforcement Learning Jobs in Washington

EchoStar Corporation

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 ...

Bright Vision Technologies

Applied RL Engineer

Reston, VA · On-site

$100 - $150/hr

The role requires deep familiarity with modern reinforcement learning algorithms, simulation environments, reward modeling, and the engineering complexity of training and evaluating policies at scale.

New

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.

The MITRE Corporation

Senior AI Security Engineer

Mclean, VA · On-site

$117K - $161K/yr

Hands-on experience with one or more of the following technical areas: agentic AI, deep reinforcement learning, computer vision, generative AI * Hands-on experience with one or more of the following ...

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Internship Deep Reinforcement Learning information

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 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 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 are the most commonly searched types of Deep Reinforcement Learning jobs in Washington?

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Infographic showing various Internship Deep Reinforcement Learning job openings in Washington as of June 2026, with employment types broken down into 18% As Needed, 27% Full Time, 9% Part Time, 18% Temporary, and 28% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Applied Researcher I (AI Foundations, LLM Customization, Finetuning, Reinforcement Learning)

Capital One

Mclean, VA • On-site

Full-time

Re-posted 20 days ago

Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

93rd of 171 rated banks

Job description

Applied Researcher I (AI Foundations, LLM Customization, Finetuning, Reinforcement Learning)
Overview:
At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.
Team Description:
The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business.
In this role, you will:
  • Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money.
  • Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data.
  • Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation.
  • Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences.
  • Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

The Ideal Candidate:
  • You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.
  • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
  • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.
  • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.
  • Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
  • Has a deep understanding of the foundations of AI methodologies.
  • Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF.
  • An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes.
  • Experience in delivering libraries, platform level code or solution level code to existing products.
  • A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects.
  • Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects.

Basic Qualifications:
  • Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research

Preferred Qualifications:
  • PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields
  • LLM
    • PhD focus on NLP or Masters with 5 years of industrial NLP research experience
    • Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization)
    • Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens)
    • Publications in deep learning theory
    • Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR
  • Finetuning
    • PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning)
    • Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance
    • Experience deploying a fine-tuned large language model
  • Data Preparation
    • Publications studying tokenization, data quality, dataset curation, or labeling
    • Contribution to a major open source corpus
    • Contribution to open source libraries for data quality, dataset curation, or labeling

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
Cambridge, MA: $218,700 - $249,600 for Applied Researcher I
McLean, VA: $218,700 - $249,600 for Applied Researcher I
New York, NY: $238,600 - $272,300 for Applied Researcher I
San Jose, CA: $238,600 - $272,300 for Applied Researcher I
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days.
No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.
If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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