About this role
Applied Researcher II focusing on AI Foundations, LLM Core and Agentic AI to build production-ready AI systems for Capital One. Collaborates with data scientists, software engineers, and product managers to translate state-of-the-art AI into customer-facing banking experiences.
Key Responsibilities
- Partner with cross-functional team to deliver AI-powered products
- Build AI foundation models through design, training, evaluation, validation, and implementation
- Engage in high-impact applied research to push AI into production customer experiences
- Translate complexity of work into tangible business goals
- Deliver libraries or platform-level code to existing products
Technical Overview
Work involves building foundation models and large language models using PyTorch, AWS Ultraclusters, HuggingFace, and VectorDBs; emphasizes training, evaluation, validation, and deployment at scale with a focus on explainability and robustness.
Ideal Candidate
The ideal candidate is a senior/mid-senior AI researcher with hands-on experience building and deploying foundation models and LLMs at scale, strong publication record, and ability to own a research agenda. Must translate research into production-impacting customer experiences and lead cross-functional collaboration.
Must-Have Skills
PhD in Electrical EngineeringComputer EngineeringComputer ScienceAIMathematicsor related fields; or MS in Electrical EngineeringComputer EngineeringComputer ScienceAIMathematicsor related fields with requirement to obtain by start date + 2 years of experience in Applied Research or MS + 4 years of experience in Applied ResearchExperience building large deep learning models and one or more of: training optimizationself-supervised learningrobustnessexplainabilityRLHFAbility to own and pursue a research agenda with autonomous long-running projectsHands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms
Nice-to-Have Skills
PhD in Computer ScienceMachine LearningComputer EngineeringApplied MathematicsElectrical Engineering or related fieldsLLMPhD focus on NLP or Masters with 5 years of industrial NLP research experiencePublications in ACL/NAACL/EMNLPNeurIPSICML or ICLRMultiple publications on pre-training of large language modelsExperience training a 10B+ parameter modelCompiler designFinetuning LLMs (supervised/instruction tuning)
Tools & Platforms
PyTorchHuggingFaceLightningVectorDBsAmazon Web ServicesAWS Ultraclusters
Required Skills
PyTorchHuggingFaceVectorDBsFoundation modelsLarge language modelsPythonAmazon Web ServicesAWS UltraclustersRLHFSelf-supervised learningExplainabilityRobustnessTraining optimizationNLPLarge DL modelsOpen-source toolsCloud computing
Hard Skills
PyTorchPythonAmazon Web ServicesAWS UltraclustersHuggingFaceVectorDBsFoundation modelsMachine LearningDeep LearningRLHFSelf-supervised learningExplainabilityRobustnessTraining optimizationLLMLarge language models
Soft Skills
Interpersonal skillsCommunicationCollaborationProblem solvingAnalytical thinkingLeadership
Keywords for Your Resume
Applied Researcher IIAI FoundationsLLM CoreAgentic AIPyTorchAWS UltraclustersAmazon Web ServicesHuggingFaceHugging FaceLightningVectorDBsFoundation modelsMachine LearningDeep LearningRLHFSelf-supervised learningExplainabilityRobustnessTraining optimizationLLMLarge language modelsPublicationsACLNAACLEMNLPNeurIPSICMLICLRPhDMSLLM core
Deal Breakers
No PhD/MS with required applied research experience, No ability to obtain work authorization/start date sponsorship, No experience with large language models or foundation models
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