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Ai Reinforcement Learning Jobs in Virginia (NOW HIRING)

Sierra Nevada Corporation

Sr AI/ML Engineer

Herndon, VA

$107K - $147K/yr

The Senior AI/ML Engineer is a highly skilled and experienced professional responsible for leading ... Hands-on experience with reinforcement learning and real-time systems applicable to MPC.

GRVTY

AI/ML Engineer

Mclean, VA · On-site

$150K - $250K/yr

Advanced research experience in machine learning, deep learning, natural language processing, generative AI, reinforcement learning, computer vision, or related disciplines. * Experience publishing ...

GRVTY

AI/ML Engineer

Mclean, VA · On-site

$150K - $250K/yr

Advanced research experience in machine learning, deep learning, natural language processing, generative AI, reinforcement learning, computer vision, or related disciplines. * Experience publishing ...

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.

Cymertek Corporation

AI/ML Engineer

Chantilly, VA · On-site

Citizenship) Preferred : • Knowledge of reinforcement learning • Familiarity with generative AI models • Experience in edge AI implementation • Expertise in natural language processing • ...

Cymertek Corporation

AI/ML Engineer

Reston, VA · On-site

Citizenship) Preferred : • Knowledge of reinforcement learning • Familiarity with generative AI models • Experience in edge AI implementation • Expertise in natural language processing • ...

The MITRE Corporation

Lead AI and Decision Engineer

Mclean, VA · On-site

$105K - $138K/yr

Our AI-enhanced Insights and Decisions department has a need for a Lead Artificial Intelligence and ... Hands-on experience with machine learning (including deep learning and reinforcement learning), and ...

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Ai Reinforcement Learning information

What is AI reinforcement learning?

AI reinforcement learning (RL) is a type of machine learning where an agent learns to make decisions by interacting with an environment. The agent receives feedback in the form of rewards or penalties based on its actions, which it uses to improve its future performance. Reinforcement learning is widely used in applications such as robotics, game playing, recommendation systems, and autonomous vehicles. Unlike supervised learning, RL doesn't require labeled input/output pairs and learns through trial and error.

What are the key skills and qualifications needed to thrive as an AI reinforcement learning specialist?

To thrive as an AI Reinforcement Learning Specialist, you need strong expertise in machine learning, deep learning, and mathematics, usually backed by a degree in computer science, engineering, or a related field. Familiarity with programming languages like Python, frameworks such as TensorFlow or PyTorch, and experience with RL-specific libraries like OpenAI Gym are typically required. Analytical thinking, problem-solving abilities, and effective collaboration are essential soft skills for excelling in this role. These skills and qualifications are crucial for developing, optimizing, and deploying RL algorithms that solve complex, real-world problems.

What are some common challenges faced by AI reinforcement learning specialists when deploying models in real-world applications?

AI Reinforcement Learning (RL) specialists often encounter challenges such as ensuring the reliability and safety of RL agents outside of controlled environments. Real-world data can be noisy and unpredictable, making it difficult for models trained in simulations to generalize. Additionally, RL algorithms typically require significant computational resources and time for training, which can be a constraint in fast-paced projects. Collaboration with domain experts and software engineers is essential to adapt algorithms to production systems and continuously monitor performance for unexpected behaviors.

What is the difference between Ai Reinforcement Learning vs Data Scientist?

AspectAi Reinforcement LearningData Scientist
Required CredentialsDegree in Computer Science, AI, or related fields; knowledge of algorithmsDegree in Statistics, Data Science, or related fields; programming skills
Work EnvironmentResearch labs, AI development teams, tech companiesBusiness analytics, data analysis teams, consulting firms
Industry UsageAI product development, autonomous systems, roboticsBusiness insights, predictive modeling, data analysis
Common Search/ComparisonYesYes

Ai Reinforcement Learning focuses on developing algorithms that enable machines to learn through trial and error to make decisions. Data Scientists analyze data to extract insights and build predictive models. While both roles require programming skills and a background in data or algorithms, reinforcement learning specialists primarily work on AI systems that learn from interactions, whereas Data Scientists focus on interpreting data to inform business decisions.

What are popular job titles related to Ai Reinforcement Learning jobs in Virginia?

For Ai Reinforcement Learning jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Ai Reinforcement Learning jobs in Virginia look for?

The top searched job categories for Ai Reinforcement Learning jobs in Virginia are:

What cities in Virginia are hiring for Ai Reinforcement Learning jobs?

Cities in Virginia with the most Ai Reinforcement Learning job openings:

Ai Reinforcement Learning jobs near you
Infographic showing various Ai Reinforcement Learning job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

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

Capital One

Mclean, VA • On-site

Full-time

Re-posted 18 days ago

Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

91st 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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