AI / ML Architect SR

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 company's 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 programming and testing
Experience on deployment in AWS or GCP

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 company's 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 programming and testing
Experience on deployment in AWS or GCP

You'll need to have:
- Minimum 6 years of experience in one or more of Data Science, LLM, Gen AI
- Master's 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