Contributed to the development and deployment of advanced large language models used across OpenAI’s product ecosystem.
Implemented scalable backend services and APIs for real-time model inference and user interaction.
Led model fine-tuning and prompt optimization efforts for safety, alignment, and performance.
Designed internal tools to evaluate, benchmark, and visualize model behavior.
Collaborated with research and product teams to integrate ML features into end-user applications.
Reduced LLM inference latency by 35% through code and infrastructure optimizations.
Authored internal research documentation on prompt engineering strategies adopted across teams.
Participated in a cross-functional team that shipped major releases of the ChatGPT platform.
Developed backend services and APIs supporting client applications in finance and healthcare sectors.
Integrated machine learning models for real-time analytics, fraud detection, and user behavior prediction.
Collaborated with data science teams to improve model training pipelines and feature engineering.
Automated CI/CD workflows, significantly reducing deployment overhead.
Increased deployment speed by 40% through CI/CD improvements.
Implemented robust logging and monitoring tools for API performance analysis.
Computer Science professional with 7 years of experience in software engineering, machine learning, and artificial intelligence. Former contributor at OpenAI, with a strong background in developing scalable AI systems, APIs, and backend architectures. Expertise in large language models (LLMs), cloud infrastructure, and end-to-end ML workflows. Adept at collaborating in agile teams to deliver impactful, real-world applications of cutting-edge technology.
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