Responsibilities:
• Design, develop, and implement data extraction systems using Large Language Models (LLMs) such as GPT-4.
• Collaborate with data scientists, engineers, and product managers to understand data extraction requirements and objectives.
• Fine-tune and customize LLMs for specific data extraction tasks, ensuring high accuracy and efficiency.
• Create and maintain data pipelines for the extraction, processing, and storage of large datasets.
• Conduct performance testing and optimization of LLMs to enhance data extraction capabilities.
• Develop and document best practices for LLM-based data extraction processes.
• Stay updated with the latest advancements in AI and LLM technologies to continually improve data extraction methodologies.
• Troubleshoot and resolve issues related to data extraction processes and models.
Qualifications:
• Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field.
• Proven experience with LLMs and natural language processing (NLP) technologies.
• Proficiency in programming languages such as Python, with experience in AI/ML libraries (e.g., TensorFlow, PyTorch).
• Strong understanding of data structures, algorithms, and software engineering principles.
• Experience with data extraction, ETL processes, and database management.
• Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Strong communication skills, both written and verbal, to effectively convey technical concepts to non-technical stakeholders.
Preferred Skills:
• Experience with transformer-based models like GPT-4, BERT, etc.
• Knowledge of big data technologies (e.g., Hadoop, Spark) and data warehousing solutions.
• Understanding of regulatory and compliance requirements related to data handling and privacy.
• Prior experience in developing and deploying machine learning models in production environments.
Location: Dallas, TX
Posted: Aug. 15, 2024, 6:11 a.m.
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