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Senior AI / ML Engineer (Python)

ITTConnect

  • Charlotte, North Carolina
  • 9 days ago

    Highlights

    ITTConnect is seeking an experienced Senior AI / ML Engineer (Python) to work for a client that is a global leader in consulting, digital transformation, technology and engineering services present in nearly 50 countries. We are seeking a highly experienced senior AI Engineer, designing scalable LLM and NLP solutions for high-volume customer interactions.

    Numbers & Facts

    LocationCharlotte, North Carolina
    Websitehttp://www.ittconnect.com

    Description

    ITTConnect is seeking an experienced Senior AI / ML Engineer (Python) to work for a client that is a global leader in consulting, digital transformation, technology and engineering services present in nearly 50 countries. End client is in the telecom industry. 

    Job location: Charlotte, NC.


    We are seeking a highly experienced senior AI Engineer, designing scalable LLM and NLP solutions for high-volume customer interactions. This role will drive architecture, best practices, and innovation across voice AI systems.


    Key Responsibilities:
    • Architect and develop AI-driven IVR and conversational systems using Python
    • Build NLP models for text classification and clustering to support intent detection and call routing
    • Perform data analysis using SQL 
    • Design and deploy LLM workflows (prompt engineering, RAG, evaluation) for voice and chat use cases
    • Lead development of Agentic AI workflows for multi-step customer interactions
    • Establish LLMOps best practices, including monitoring, evaluation, and lifecycle management
    • Partner with IVR platform, speech engineering, and product teams
    • Mentor offshore and junior AI engineers

    Requirements

    • 12+ years of experience in AI / ML
    • Strong proficiency in Python.
    • Proven expertise in NLP, including:
      • Text classification
      • Clustering
    • Strong experience in data analysis using SQL
    • Hands-on experience with LLMs:
      • Prompt engineering
      • Evaluation frameworks
      • Retrieval-Augmented Generation (RAG)

    Good to Have:

    • Experience with Agentic AI and multi-agent orchestration
    • Experience with LLMOps / MLOps in production environments
    • Cloud Experience

    Libraries & Tools:

    • Python / ML: NumPy, Pandas, Scikit-learn, XGBoost
    • NLP: spaCy, Hugging Face Transformers, NLTK, Sentence-Transformers
    • LLM Frameworks: LangChain, LlamaIndex, OpenAI SDK
    • Agentic AI (Good to Have): LangGraph, AutoGen, CrewAI
    • Data & SQL:  Oracle, MySQL, SQLAlchemy
    • Vector Databases: FAISS, Pinecone, Weaviate, Qdrant
    • LLMOps / MLOps (Good to Have): MLflow, Weights & Biases, BentoML, Airflow

     



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