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$187,500–$254,750.
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
2107 open roles
on FindRole.
Listed pay typically runs
$197,300–$225,100
across 1107 roles with salary data.
The Applied Researcher I (AI Foundations) joins the AI Foundations team to develop trustworthy and reliable artificial intelligence systems. This role involves partnering with cross-functional teams of data scientists, software engineers, and product managers to deliver AI-powered products. The researcher will build AI foundation models through all phases of development, including design, training, evaluation, validation, and implementation. Key responsibilities include conducting high-impact applied research to translate complex AI developments into tangible business goals. The position requires proficiency with a technology stack including Pytorch, AWS Ultraclusters, Huggingface, Lightning, and VectorDBs. The work focuses on revealing insights within large volumes of numeric and textual data to solve business problems and create the next generation of customer experiences through scalable, high-performance AI infrastructure.
Build AI foundation models through all phases of development including design, training, evaluation, and implementation.
Conduct high-impact applied research to integrate the latest AI developments into customer experiences.
Leverage technologies like PyTorch, AWS Ultraclusters, and VectorDBs to extract insights from large datasets.
Deliver AI-powered products by partnering with cross-functional teams of data scientists and engineers.
Own and pursue a research agenda by identifying impactful problems and carrying out long-running projects.
Translate complex technical work into tangible business goals for stakeholders.
Deliver libraries, platform-level code, or solution-level code to existing products.
What we're looking for
Currently hold or are in the process of obtaining a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field.
Possess an M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or a related field plus 2 years of experience in Applied Research.
Have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms.
Possess a deep understanding of the foundations of AI methodologies.
Have experience building large deep learning models for language, images, events, or graphs.
Demonstrate expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF.
Have a track record of delivering models at scale in terms of training data and inference volumes.
Have experience delivering libraries, platform-level code, or solution-level code to existing products.
Pytorch
AWS
Huggingface
Lightning
VectorDBs
LLM
NLP
Deep Learning
RLHF
Quantization
Model Sparsification
Training Parallelism
Supervised Finetuning
Instruction-Tuning
Transfer Learning
Pytorch
AWS
Huggingface
Lightning
VectorDBs
LLM
NLP
Deep Learning
RLHF
Quantization
Model Sparsification
Training Parallelism
Supervised Finetuning
Instruction-Tuning
Transfer Learning
Pytorch
AWS
Huggingface
Lightning
VectorDBs
LLM
NLP
Deep Learning
RLHF
Quantization
Model Sparsification
Training Parallelism
Supervised Finetuning
Instruction-Tuning
Transfer Learning
Pytorch
AWS
Huggingface
Lightning
VectorDBs
LLM
NLP
Deep Learning
RLHF
Quantization
Model Sparsification
Training Parallelism
Supervised Finetuning
Instruction-Tuning
Transfer Learning
Pytorch
AWS
Huggingface
Lightning
VectorDBs
LLM
NLP
Deep Learning
RLHF
Quantization
Model Sparsification
Training Parallelism
Graph Neural Networks
Sequential Models
Multivariate Time Series
Supervised Finetuning
Instruction-Tuning
Transfer Learning
Tokenization