Request Technology - Chicago, IL

posted 10 days ago

Full-time - Mid Level
Chicago, IL
Administrative and Support Services

About the position

The AI Engineer will focus on AI engineering, natural language processing, and machine learning to design, develop, and deploy innovative solutions that utilize both structured and unstructured data. This role is crucial for developing cutting-edge legal AI solutions that enhance efficiency and decision-making across various business groups and legal practices.

Responsibilities

  • Develop and implement cutting-edge legal AI solutions that drive efficiency and improve decision making.
  • Prototype and test AI solutions using Python and Streamlit, focusing on natural language processing and text extraction from documents.
  • Develop plugins and assistants using LangChain, LlamaIndex, or Semantic Kernel, with expertise in prompt engineering and semantic function design.
  • Design and implement Retrieval Augmented Generation (RAG) stores using classic information retrieval and semantic embeddings.
  • Develop and deploy agents using AutoGen, CrewAI, LangChain Agents, and LlamaIndex Agents.
  • Use Gen AI to distill metadata and insights from documents.
  • Fine-tune LLMs to optimize for domain and cost.
  • Collaborate with stakeholders to implement and automate AI-powered solutions for common business workflows.
  • Enhance documentation procedures, codebase, and adherence to best practices.

Requirements

  • Bachelor's Degree in Computer Science, Engineering, or related field.
  • A minimum of 5 years of experience in AI engineering or a related field.
  • Proven experience with AI engineering tools and technologies, including Python, Streamlit, Jupyter Notebooks, Langchain, LlamaIndex, and Semantic Kernel.
  • Experience with natural language processing, text extraction, and information retrieval techniques.
  • Strong understanding of machine learning and deep learning concepts, including transformer-based GPT models.
  • Experience with distributed computing and cloud environments (e.g., Microsoft Azure).
  • Solid understanding of large language models.

Nice-to-haves

  • Enterprise level experience, big accounting firms, academia.
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