✦ Luna Orbit — AI & Machine Learning

Senior Manager, Data Science - LLM Customization Team

at Discover Financial Services

📍 3 Locations Unknown 💰 $229K – $262K USD / year Posted April 17, 2026
Salary $229K – $262K USD / year
Type Not Specified
Experience senior
Exp. Years Not specified
Education Not specified
Category AI & Machine Learning

As Senior Manager, Data Science - LLM Customization Team, you will lead work that brings LLM and generative AI vision to life. You will partner cross-functionally to build and operationalize NLP and LLM solutions for business-specific customer experiences and features.

  • Partner with cross-functional team to deliver AI powered products that change customer interactions
  • Leverage Pytorch, Hugging Face, AWS Ultraclusters, LangChain, VectorDBs to extract insights from numeric and textual data
  • Serve as expert in Natural Language Processing (NLP) to adapt and finetune Large Language Models (LLMs) for business-specific applications
  • Build NLP models through design, training, evaluation, and validation; operationalize with engineering teams
  • Translate the complexity of your work into tangible business goals

The technical scope includes Natural Language Processing (NLP) and Large Language Models (LLMs), including adapting and fine-tuning them for business-specific applications. The stack emphasizes Pytorch, Hugging Face, AWS Ultraclusters, LangChain, and VectorDBs, with model development across design, training, evaluation, validation, and production operationalization for scalable and resilient systems.

The ideal candidate is a senior data science manager who leads an LLM customization team focused on Natural Language Processing (NLP) and generative AI. They have hands-on experience fine-tuning Large Language Models (LLMs) for business-specific applications using open-source tools and cloud platforms, and they can operationalize models into scalable, resilient production systems with stacks including Pytorch, Hugging Face, AWS Ultraclusters, LangChain, and VectorDBs.

Natural Language Processing (NLP)Large Language Models (LLMs)adapt and finetune them for business specific applicationsbuild NLP models through all phases of development (design through trainingevaluationand validation)operationalize models in scalable and resilient production systemshands-on experience working with LLMsPytorchHugging FaceAWS UltraclustersLangChainVectorDBs
PytorchHugging FaceAWS UltraclustersLangChainVectorDBs
Natural Language Processing (NLP)Large Language Models (LLMs)fine-tuningPytorchHugging FaceAWS UltraclustersLangChainVectorDBsmodel development lifecycle (designtrainingevaluationvalidation)operationalize production systems
Natural Language Processing (NLP)Large Language Models (LLMs)gen generative AIfine-tuningNatural Language Processing (NLP) modelsmachine learning engineers collaborationlanguage modelsopen-source toolscloud computing platformsPytorchHugging FaceAWS UltraclustersLangChainVectorDBsmodel development lifecycle (design through trainingevaluationand validation)operationalize modelsscalable and resilient production systemsresearch life cycle (from research to building production systems)
cross-functional collaborationtranslating complexity into tangible business goalscreative problem solvingasking questionsdriving definition for ambiguous problemsinnovationinfluencestaying current on state-of-the-art methodsexperimenting and innovating
Industry Banking
Job Function Lead LLM customization and NLP model development and operationalization for generative AI products.
Role Subtype Data Scientist
Tech Domains Amazon Web Services, AI & Machine Learning, Natural Language Processing, Python
Senior ManagerData Science - LLM Customization TeamData ScienceLLM CustomizationNatural Language Processing (NLP)NLPLarge Language Models (LLMs)LLMsgenAIgenerative AIfine-tunefinetunePytorchHugging FaceAWS UltraclustersLangChainVectorDBsevaluationvalidationtrainingoperationalizescalable and resilient production systemsopen-source toolscloud computing platforms

Hands-on experience fine-tuning Large Language Models (LLMs), Experience with Natural Language Processing (NLP) model development lifecycle, Must have used Pytorch and Hugging Face for LLM/NLP work, Must have used LangChain and VectorDBs, Must have used AWS Ultraclusters or AWS cloud infrastructure for LLM workloads

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