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Machine Learning AI_W_Bentonville AR

Job in Bentonville, Benton County, Arkansas, 72712, USA
Listing for: Chelsoft Solutions Co.
Full Time position
Listed on 2025-12-01
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist, Data Engineer
Job Description & How to Apply Below
Position: Machine Learning AI_W2_Bentonville AR

Overview

We are seeking a highly skilled and innovative Machine Learning / AI Engineer to design and build a new AI. This agent will streamline workflows by enabling users to request data directly—without needing to search for it manually.

This is a hands-on engineering role focused on building intelligent, scalable, and user-friendly AI solutions using the latest in LLM, Generative AI, and agentic frameworks.

Responsibilities
  • Architect and develop a custom AI agent capable of understanding natural language queries and retrieving relevant data.
  • Integrate Large Language Models (LLMs) and Generative AI capabilities to enhance user experience.
  • Utilize Lang Chain to orchestrate agent workflows and tool integrations.
  • Build and maintain data pipelines using Python and Looker ML for real-time data access and visualization.
  • Collaborate with cross-functional teams to understand associate needs and translate them into technical solutions.
  • Ensure scalability, security, and performance of AI systems in production environments.
Required Skills & Experience
  • Proven experience building AI agents or chatbots using LLMs and Lang Chain.
  • Strong proficiency in Python for ML development and API integration.
  • Familiarity with Generative AI concepts and tools.
  • Experience with Looker ML or similar BI/ML platforms.
  • Understanding of retrieval-augmented generation (RAG) and agentic AI workflows.
  • Ability to work independently and communicate effectively with technical and non-technical stakeholders.
Preferred Qualifications
  • Experience deploying AI solutions in enterprise environments.
  • Knowledge of cloud platforms (AWS, Azure, GCP).
  • Familiarity with vector databases and embedding models.
  • Background in NLP, data engineering, or MLOps.
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