Position Details
About this role
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.
Key Responsibilities
- 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
Technical Overview
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.
Ideal Candidate
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.
Must-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
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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