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@marissagomez
AI Prompt Engineer focused on enhancing AI performance through prompt development.
As an AI Prompt Engineer, I specialize in enhancing AI performance through effective prompt development. My work has led to a remarkable 30% increase in accuracy for generating user-focused content by collaborating with cross-functional teams. Additionally, I have successfully reduced response time by 25% through A/B testing of prompt structures, showcasing my ability to translate user requirements into actionable prompts.
At GlobalLogic, I developed and refined prompts for various AI models, ensuring clarity and relevance to meet user needs. My commitment to driving innovation has improved team efficiency and project delivery speed. I also created comprehensive documentation and guidelines for prompt engineering best practices, which have been instrumental in enhancing consistency across projects.
Currently, I am furthering my expertise as an AI Prompt Trainer at Outlier, where I have implemented personalized training programs that resulted in a 25% increase in model accuracy. My passion for continuous improvement and education is reflected in my workshops and training sessions designed to empower team members with best practices for effective AI prompt training.
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Work history, roles, and key accomplishments
AWS
Aug 2023 - Present (2 years 3 months)
Implemented scalable cloud infrastructure solutions using AWS services to optimize performance. Managed AWS resources for high availability and security, and automated tasks to improve efficiency.
Outlier
Jan 2022 - Present (3 years 10 months)
Developed personalized training programs for AI algorithms, resulting in a 25% increase in model accuracy. Collaborated with data scientists to improve AI prompt responses and conducted workshops on best practices.
GlobalLogic
Developed and refined prompts for various AI models, ensuring clarity and relevance to meet user needs. Collaborated with cross-functional teams to enhance AI performance, achieving a 30% increase in accuracy and a 25% reduction in response time through A/B testing.
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