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This listing doesn't post a salary. Most similar roles pay
$202,800–$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, VLM) joins the AI Foundations team to develop trustworthy and reliable AI systems. This role involves partnering with a cross-functional team of data scientists, software engineers, and product managers to build AI-powered products that transform how customers interact with their money. You 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 push the latest AI developments into next-generation customer experiences. You will utilize a technology stack including Pytorch, AWS Ultraclusters, Huggingface, Lightning, and VectorDBs to analyze large volumes of numeric and textual data. The work focuses on solving complex business problems by applying state-of-the-art AI methodologies to create scalable, high-performance infrastructure.
Build AI foundation models through all phases of development including design, training, evaluation, and implementation.
Leverage technologies like PyTorch, AWS Ultraclusters, and Huggingface to extract insights from large numeric and textual datasets.
Conduct high-impact applied research to integrate the latest AI developments into next-generation customer experiences.
Deliver AI-powered products by collaborating with data scientists, software engineers, and product managers.
Own and pursue a research agenda by identifying impactful problems and autonomously carrying out long-running projects.
Develop and deliver libraries, platform-level code, or solution-level code for existing products.
Optimize large deep learning models for training and inference at scale.
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.
Demonstrate experience building large deep learning models for language, images, events, or graphs.
Possess expertise in training optimization, self-supervised learning, robustness, explainability, or RLHF.
Maintain a track record of delivering models at scale in terms of training data and inference volumes.
Demonstrate a track record of high-quality machine learning ideas through accomplishments such as first-author publications or projects.
Possess the ability to own and pursue a research agenda, including choosing impactful problems and autonomously carrying out long-running projects.
Pytorch
AWS
Huggingface
Lightning
LLM
NLP
Deep Learning
RLHF
Quantization
Model Sparsification
Training Parallelism
Supervised Finetuning
Instruction-Tuning
Transfer Learning
Tokenization
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