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AI Solutions Architect

2 months ago


Peachtree City, Georgia, United States Datamtx LLC Full time

Position:
AI Solutions Architect

100% remote
Rate / salary is competitive

Overview:


Datamtx LLC is on the lookout for a skilled and knowledgeable AI Solutions Architect to become a vital part of our innovative team, driving advancements in AI technology.

In this position, you will be responsible for the design and implementation of state-of-the-art large language models (LLMs) for practical applications.

Key Responsibilities:
  • AI Solution Development: Create and deploy inventive solutions utilizing large language models (LLMs).
  • Refine existing LLMs using proprietary datasets to enhance their performance and adapt them for new use cases.
  • Establish and execute training pipelines for LLMs, focusing on efficiency and precision.

Text Generation Model Development: Design, develop, and maintain high-quality text generation models by implementing and assessing various LLM architectures (e.g., Transformers, BERT) tailored for specific tasks.

  • Train and fine-tune models on diverse datasets to achieve peak performance.
  • Optimize model parameters through iterative experimentation and fine-tuning methodologies.

RAG Model Implementation: Design, develop, and deploy Retrieval-Augmented Generation (RAG) models for producing high-quality text based on user prompts or queries.

  • Assess the performance of RAG models using various evaluation metrics.
  • Analyze and interpret model outputs to identify improvement opportunities and enhance model performance.

AI-Powered Agent Development: Create and integrate AI-driven agents capable of engaging in conversations with users utilizing the developed RAG models.

  • Incorporate natural language understanding (NLU) capabilities to enable agents to comprehend user inputs and respond appropriately.
  • Develop and refine dialogue management systems to control agent interactions and ensure coherence.

Data Preparation and Model Fine-tuning: Prepare and curate extensive text datasets for training and validating language models.

  • Implement LLM fine-tuning strategies using various optimization algorithms (e.g., Adam, SGD).
  • Develop and apply data augmentation techniques to enhance model generalization.

Model Evaluation and Enhancement: Create and implement metrics for assessing the performance of LLMs based on specific project objectives (e.g., accuracy, fluency, coherence).

  • Analyze and interpret model outputs to identify areas for enhancement.

Continuous Learning: Stay informed about the latest advancements in LLMs and emerging trends in natural language processing (NLP) and deep learning.


Qualifications:
  • Required: Minimum of 5 years of experience in software engineering with a strong emphasis on NLP and machine learning applications.
  • Demonstrated expertise in constructing and deploying large language models (LLMs) using frameworks such as TensorFlow, PyTorch, or other relevant tools.

Preferred:
  • Experience with various LLM architectures (e.g., BERT, Transformer).
  • Strong grasp of natural language processing principles.
  • In-depth understanding of advanced RAG techniques.
  • Familiarity with NLP libraries (e.g., spaCy, NLTK) and methodologies for fine-tuning and integrating LLMs into diverse applications.

Skills:
  • Proficiency in programming language: Python.

Experience with LLM Frameworks:
  • Experience with at least one of the following: TensorFlow, PyTorch, Hugging Face Transformers, etc.