GenAI Lead with Data Warehouse Expertise at Dallas, TX Onsite

Overview

On Site
Depends on Experience
Full Time

Skills

("GEN" or "Generative")
("AI" or "Artificial Intelligence")
("Data ware" or "Dataware" or "DataBricks" or "Data Bricks")
(("Large Language Model" or "LLM" or "ML" or "Machine Learning")
(Lead or Architect)

Job Details

About Infinite:

Infinite is a global leader in digital engineering and IT services, with over 20 years of experience driving digital transformation. We partner with leading Fortune 1000 companies to deliver innovative, scalable technology solutions that accelerate business outcomes.

With deep expertise in telecommunications, healthcare, banking, and finance, Infinite helps organizations optimize and modernize their technology landscapes to achieve long-term growth and efficiency.

Job Description:
We are seeking a highly skilled and hands-on GenAI Lead with a strong background in Data Warehousing to join our team. The ideal candidate will have experience in building and deploying Generative AI solutions and a solid understanding of data engineering principles. Experience with Databricks is a strong advantage.

Key Responsibilities:

  • Design, develop, and deploy Generative AI models and solutions for enterprise use cases.
  • Resource should have 12+ Years of experience
  • Collaborate with data engineers and data scientists to integrate AI models with existing data warehouse systems.
  • Build and optimize data pipelines to support AI/ML workloads.
  • Work with large datasets to extract insights and train models.
  • Ensure scalability, performance, and reliability of AI solutions in production environments.
  • Stay updated with the latest advancements in GenAI and data engineering technologies.

Required Skills:

  • 3+ years of hands-on experience in developing and deploying Generative AI models (e.g., LLMs, transformers, diffusion models).
  • Strong programming skills in Python and experience with AI/ML frameworks such as PyTorch, TensorFlow, or Hugging Face.
  • Solid understanding of data warehouse concepts and experience with platforms like Snowflake, Redshift, or BigQuery.
  • Experience in building and maintaining ETL/ELT pipelines.
  • Familiarity with MLOps practices and tools.

Preferred Qualifications

  • Experience with Databricks for data engineering and ML model development.
  • Knowledge of cloud platforms (AWS, Azure, or Google Cloud Platform).
  • Experience with vector databases and retrieval-augmented generation (RAG) techniques.
  • Strong problem-solving skills and ability to work in a fast-paced environment.
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