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AI Solutions Architect

2 months ago

Peachtree Corners, Georgia, United States DATAMTX LLC Full time

Position:

AI Solutions Architect Please review all relevant application materials thoroughly before proceeding with the application process.

100% remote
Compensation is competitive.
Overview:

We are in search of a skilled and knowledgeable AI Solutions Architect to become a vital part of our expanding team, dedicated to advancing the frontiers of AI technology.

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

Key Responsibilities:
Develop and implement AI solutions: Create and deploy innovative applications utilizing large language models (LLMs).
Refine existing LLMs on proprietary datasets to enhance performance and adapt them for new use cases.
Construct and execute training pipelines for LLMs, focusing on efficiency and precision.

Design, develop, and maintain high-quality text generation models: Assess and implement various LLM architectures (e.g., Transformers, BERT) tailored for specific tasks.

Train and optimize models on diverse datasets to achieve peak performance.
Fine-tune model parameters through iterative experimentation and optimization techniques.

Design, develop, and deploy Retrieval-Augmented Generation (RAG) models for producing high-quality text based on user inputs or queries.
Assess and implement various RAG architectures for targeted tasks and applications.
Measure the performance of RAG models using a variety of metrics.
Analyze and interpret model outputs to identify improvement opportunities and enhance model performance.
Create and integrate AI-driven agents capable of engaging users through the developed RAG models.
Implement natural language understanding (NLU) features to enable agents to interpret user input and respond appropriately.
Develop and refine dialogue management systems to guide agent interactions and ensure coherence.

Data Preparation and Fine-tuning: Assemble and curate extensive text datasets for training and validating language models.
Apply LLM fine-tuning strategies utilizing various optimization algorithms (e.g., Adam, SGD).
Develop and implement data augmentation techniques to enhance model generalization.

Model Evaluation and Optimization:

Establish and apply metrics for assessing the performance of LLMs based on specific project objectives (e.g., accuracy, fluency, coherence).

Analyze and interpret model outputs to pinpoint areas for enhancement.

Stay informed on the latest advancements in LLMs: Proactively investigate and assess new research in the LLM domain.
Keep up with emerging trends in natural language processing (NLP) and deep learning.

Qualifications:
Required: 5+ years of experience in software development 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:
Familiarity with various LLM architectures (e.g., BERT, Transformer).
Strong grasp of natural language processing principles.
In-depth understanding of advanced RAG techniques.
Experience with NLP libraries (e.g., spaCy, NLTK) and methods for fine-tuning and integrating LLMs into diverse applications.

Skills:
Proficiency in programming language: Python.

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