Capital One
Staff Applied Researcher
$306K–$381K
San Francisco, CA +4 · Staff · Full-time · Posted Oct 5, 2026
- Location
- San Francisco, CA
McLean, VA
Cambridge, MA
San Jose, CA
New York, NY - Experience
- 4 years of Applied Research experience with a PhD, or 6 years with an M.S.; additional specialized experience is listed as preferred.
- Education
- PhD or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
About the job
Leads applied AI research and foundation-model development, translating research into scalable, deployable products and guiding research direction across teams.
What you'll do
- Partner with data scientists, engineers, and product managers to deliver AI-powered products.
- Build AI foundation models through design, training, evaluation, validation, and implementation.
- Set research direction, mentor applied scientists, and translate research into deployable capabilities.
What they ask for
- PhD in a listed related field plus 4 years of Applied Research experience, or an M.S. in a listed related field plus 6 years of Applied Research experience.
- Hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
- Deep understanding of AI methodologies and experience building large deep learning models.
- Track record of delivering models at scale and delivering code or libraries to existing products.
Nice to have
- Experience or publications in training optimization, self-supervised learning, robustness, explainability, or RLHF.
- Relevant research publications or experience training and deploying large language models.
Pay
$306,300 - $349,500 USD base salary; $334,100 - $381,300 USD base salary
Tools
Pytorch, AWS Ultraclusters, Huggingface, Lightning, deep speed, nemo
AI focus
Applied AI research and development of foundation models, including training, evaluation, deployment, and research in areas such as large language models, behavioral models, optimization, finetuning, and data preparation.
Model-written summary · the original posting is authoritative