AI / ML Architect SR

Overview

• Responsibilities will include but are not limited to:
• Development and testing of Generative AI solution either Agentic or non-AgenticAI
• Deep understanding of any framework either Langgraph or Autogen or CrewAI
• Deep understanding of Data preprocessing, Prompt management, Caching, Validation, Advanced RAG, RLHF and success measurement.
• Thorough understanding of LLMOps, data pipelines and other common services required to operationalize the Generative AI use cases.
• Designing end-to-end Generative AI solutions tailored to specific Verizon use cases.
• Deep understanding of automation and AI technologies and their application in business operations.
• Develop scalable prototypes of LLM and NLP Modules and systems which are critical to the companys product lines.
• Apply state-of-the-art LLM techniques to understand a large amount of unstructured data and translate them to a meaningful and structured data
• Design, develop and evaluate predictive LLM models that are on par with industry standards & define metrics that measure success and customer value delivery
• Work closely with process experts to analyze and design solutions based on business requirements.
• Technical skills :
• Develop LangGraph based Agentic Framework implementation
• Use Large Language Models for content generation
• Create Prompt templates for LLMs
• Fluent in Python, Jupyter Notebooks
• Experience in RAG pipelines / Vector Databases
• Develop Python based parsers for PDFs
• Experience on node.js programming and testing
• Experience on deployment in AWS or GCP

Responsibilities

• Responsibilities will include but are not limited to:
• Development and testing of Generative AI solution either Agentic or non-AgenticAI
• Deep understanding of any framework either Langgraph or Autogen or CrewAI
• Deep understanding of Data preprocessing, Prompt management, Caching, Validation, Advanced RAG, RLHF and success measurement.
• Thorough understanding of LLMOps, data pipelines and other common services required to operationalize the Generative AI use cases.
• Designing end-to-end Generative AI solutions tailored to specific Verizon use cases.
• Deep understanding of automation and AI technologies and their application in business operations.
• Develop scalable prototypes of LLM and NLP Modules and systems which are critical to the companys product lines.
• Apply state-of-the-art LLM techniques to understand a large amount of unstructured data and translate them to a meaningful and structured data
• Design, develop and evaluate predictive LLM models that are on par with industry standards & define metrics that measure success and customer value delivery
• Work closely with process experts to analyze and design solutions based on business requirements.
• Technical skills :
• Develop LangGraph based Agentic Framework implementation
• Use Large Language Models for content generation
• Create Prompt templates for LLMs
• Fluent in Python, Jupyter Notebooks
• Experience in RAG pipelines / Vector Databases
• Develop Python based parsers for PDFs
• Experience on node.js programming and testing
• Experience on deployment in AWS or GCP

Requirements

Youll need to have:

• Minimum 6 years of experience in one or more of Data Science, LLM, Gen AI
• Masters degree from an accredited college or university preferred
• Established experience delivering information management solutions to large numbers of end users
• Experience in building LLM solutions to business problems across support, sales, digital, chat, voice etc.,
• Familiarity with Gen AI Models (OpenAI, Gemini AI, Vertex.AI, Mistral, LlaMa, etc.,) and finetune based on domain specific needs
• Experience in text processing, Vector databases and embedding models
• Experience in NLP, Transformers and Neural Networks
• Hands-on experience in using Langchain and good exposure to LLMOps
• Strong independent and creative research skills necessary to keep up with the latest trends in advanced analytics and ML
• Research, recommend and implement best practices of LLM and NLP systems that can scale
• Identify new process opportunities, while quickly assessing feasibility
• Excellent written and verbal communication skills able to effectively communicate technical details to a non-technical audience as well as produce clear and concise written documentation