Machine Learning AI Engineer - W2 (NO C2C, 1099) - Bentonville, AR - Posted by Tauqeer

Overview

On Site
Hybrid
$50 - $60
Contract - W2
Contract - 6 Month(s)
No Travel Required

Skills

Large Language Models (LLMs)
Machine Learning (ML)
Generative Artificial Intelligence (AI)
LangChain
Python
API
Machine Learning Operations (ML Ops)

Job Details

Required Skills:
LLM GenAI LangChain Looker ML Python

Overview:
We are seeking a highly skilled and innovative Machine Learning / AI Engineer to design and build a new AI agent that supports Sam s Home Office associates. 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.
Key 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 LangChain 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 LangChain.
  • 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, Google Cloud Platform).
  • Familiarity with vector databases and embedding models.
  • Background in NLP, data engineering, or MLOps.
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