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$30K

$113.1K

$164.5K

How much do full time llm researcher jobs pay per year?

As of Aug 16, 2026, the average yearly pay for full time llm researcher in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a full time LLM researcher?

To thrive as a Full Time LLM Researcher, you need a deep understanding of machine learning, natural language processing, and large language model architectures, often supported by an advanced degree in computer science or a related field. Proficiency with Python, deep learning frameworks (like PyTorch or TensorFlow), and experience using large-scale compute resources are typically required. Strong analytical thinking, problem-solving abilities, and clear communication help researchers articulate findings and collaborate effectively. These skills ensure high-impact research, innovative model development, and effective integration of new technologies into real-world applications.

What does a full time LLM researcher do?

A Full Time LLM Researcher studies and develops large language models (LLMs), such as those used in artificial intelligence and natural language processing applications. Their work often involves designing experiments, training models on large datasets, evaluating model performance, and publishing research findings. They may also collaborate with engineers and data scientists to implement and optimize LLMs for real-world applications. This role typically requires strong programming skills, a background in machine learning, and expertise in natural language processing.

What are some common challenges full time LLM researchers face when collaborating with cross-functional teams?

Full Time LLM Researchers often collaborate with engineers, data scientists, and product managers to deploy and refine language models. A common challenge is communicating complex research findings to non-experts, ensuring alignment between research goals and product requirements. Balancing experimental innovation with practical constraints, such as computational resources and project deadlines, can also be demanding. Effective collaboration requires adaptability, strong communication skills, and the ability to translate theoretical advances into applied solutions.

What is the difference between Full Time Llm Researcher vs Part Time Llm Researcher?

AspectFull Time Llm ResearcherPart Time Llm Researcher
Work HoursTypically 35-40 hours per weekLess than 20 hours per week
Employment StatusFull-time employmentPart-time employment
CredentialsUsually requires an LLM degree, relevant research experienceSame as full-time, but may have more flexible qualifications
Work EnvironmentResearch institutions, law firms, universitiesSimilar environments, with flexible scheduling

Full Time Llm Researchers work full-time hours, often with more responsibilities and consistent schedules, while Part Time Llm Researchers have flexible hours with potentially fewer responsibilities. Both roles typically require an LLM degree and involve research in legal fields, but the full-time position offers more stability and engagement.

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Full Time Llm Researcher jobs near you
Infographic showing various Full Time Llm Researcher job openings in the United States as of August 2026, with employment types broken down into 95% Full Time, 1% Part Time, and 4% Contract. Highlights an 78% Physical, 5% Hybrid, and 17% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

Lead AI Engineer (FM Hosting, LLM Inference)

Capital One

Mclean, VA

$103K - $136K/yr

Full-time

Re-posted 3 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

Lead AI Engineer (FM Hosting, LLM Inference)

Overview

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. 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 continuing to build world-class applied science and engineering teams to deliver 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 Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact.

In this role, you will:

  • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.

  • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.

  • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.

  • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.

The Ideal Candidate:

  • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

  • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

  • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

  • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

  • You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Basic Qualifications:

  • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies

  • At least 4 years of experience programming with Python, Go, Scala, or Java

Preferred Qualifications:

  • 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)

  • Experience designing, developing, delivering, and supporting AI services

  • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, or Golang

  • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost

  • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production

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: $197,300 - $225,100 for Lead AI Engineer


McLean, VA: $197,300 - $225,100 for Lead AI Engineer


New York, NY: $215,200 - $245,600 for Lead AI Engineer


San Jose, CA: $215,200 - $245,600 for Lead AI Engineer








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 theCapital 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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