✦ Luna Orbit — AI & Machine Learning

Senior Lead AI Engineer (FM Hosting, LLM Inference)

at Capital One Financial

📍 4 Locations Unknown 💰 $229K – $262K USD / year Posted April 03, 2026
Salary $229K – $262K USD / year
Type Full-Time
Experience lead
Exp. Years 2+ years
Education Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research
Category AI & Machine Learning

Applied Researcher I within AI Foundations focuses on building and pushing forward AI capabilities across LLM customization, fine-tuning, and reinforcement learning for Capital One.

  • Partner with data scientists and engineers to deliver AI-powered products; Leverage PyTorch, Huggingface, and VectorDBs to build foundation models; Engage in applied research to push latest AI developments; Translate research into business goals; Communicate findings to stakeholders

Hands-on with PyTorch, Huggingface, VectorDBs, and AWS Ultraclusters; focus on foundation models, LLM inference, finetuning, and RLHF; strong ties to production-ready tooling.

The ideal candidate is an early-career or mid-level applied researcher with a PhD or Masters plus 2+ years of experience, strong foundation in AI/ML and NLP, and a track record of applying research to production-ready tools.

Bachelor's degree in Computer ScienceAIElectrical EngineeringComputer Engineeringor related fieldsAt least 6 years programming with PythonGoScalaor JavaAt least 6 years of experience developing AI and ML algorithms or technologiesAt least 4 years of experience developing AI and ML algorithms or technologies with a Master's degree
7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWSGoogle CloudAzureor equivalent private cloud)Experience designingdevelopingintegratingdeliveringand supporting complex AI systemsDemonstrated ability to lead and mentor an engineering team and influence cross-functional stakeholdersExperience developing AI and ML algorithms or technologies (e.g. LLM InferenceSimilarity Search and VectorDBsGuardrailsMemory) using PythonC++C#Javaor GolangExperience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilizationlatencythroughputand costExcellent communication and presentation skills
PytorchHuggingfaceVectorDBsNemo GuardrailsAWS Ultraclusters
PythonPyTorchHuggingfaceVectorDBsfoundation modelsLLM inferencedata sciencePyTorch LightningAWS UltraclustersNLPreinforcement learning
PythonGoScalaJavaPyTorchHuggingfaceVectorDBsNemo GuardrailsAWS Ultraclustersfoundation model trainingLLM inferenceguardrailsobservabilitymodel evaluationexperimentationgovernance
communicationleadershipteam collaborationproblem-solving
Industry Banking
Job Function Develop and operationalize AI foundation models and LLM customization techniques for Capital One.
Role Subtype AI Researcher
Tech Domains Python, Amazon Web Services, Google Cloud Platform, Linux, PyTorch, Huggingface, VectorDBs, Nemo Guardrails, PyTorch Lightning, Foundation models
Visa Sponsorship Yes
Applied Researcher IAI FoundationsLLM CustomizationFinetuningReinforcement LearningPythonPytorchHuggingfaceLightningVectorDBsAWS Ultraclustersfoundation modelsLLM inferenceguardrailsmodel trainingdata scienceresearchproductionobservabilityPyTorchLLMPytorch Lightning

Lack of hands-on experience with large language models, No track record of applied research or publications, No experience with production ML or cloud deployments

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