This role pays more than
53%
of similar roles. Most pay
$189,462–$254,750
— the shaded band above.
At the midpoint, this role pays about
$234k
versus about
$222k
for comparable roles.
Based on 240 similar postings.
Employer
About Capital One Financial
Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking
Capital One Financial currently has
998 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 992 roles with salary data.
As an Applied Researcher I (AI Foundations, LLM Core and Agentic AI), you will join the AI Foundations team to develop trustworthy and reliable AI systems for the banking industry. You will collaborate with a cross-functional team of data scientists, software engineers, and product managers to build AI foundation models through every phase of development, including design, training, evaluation, validation, and implementation. Your daily work involves uncovering insights within massive volumes of numeric and textual data to create next-generation customer experiences. To achieve these goals, you will utilize a technical stack featuring PyTorch, AWS Ultraclusters, Huggingface, Lightning, and VectorDBs. You will apply advanced methodologies such as self-supervised learning, RLHF, and training optimization while leveraging open-source tools and cloud platforms to solve complex problems regarding large deep learning models for language, images, events, or graphs.
Build AI foundation models through all phases of development including design, training, evaluation, validation, and implementation.
Conduct high-impact applied research to integrate state-of-the-art AI developments into next-generation customer experiences.
Utilize a broad technology stack including PyTorch, Hugging Face, and VectorDBs to extract insights from large datasets.
Develop scalable deep learning models for language, images, events, or graphs using open-source tools and cloud platforms.
Translate complex technical research into tangible business goals and solutions for cross-functional stakeholders.
Research and evaluate emerging technologies to identify opportunities for improving existing machine learning products.
Own and pursue a research agenda by selecting impactful problems and autonomously managing long-running projects.
What we're looking for
Must have a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field.
Alternatively, must have an M.S. in a relevant field plus 2 years of experience in Applied Research.
Must have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
Must have a deep understanding of the foundations of AI methodologies.
Must have experience building large deep learning models for language, images, events, or graphs.
Must have an engineering mindset with a track record of delivering models at scale for training data and inference volumes.
Must have a track record of high-quality ideas in machine learning, such as first author publications or projects.
Experience in training optimization, self-supervised learning, robustness, explainability, or RLHF (preferred); multiple publications on LLM pre-training (preferred).