Maxime Rivest is an AI Optimization Engineer with 11 years of experience blending data science, production ML, and developer-focused tooling to make LLMs more accessible and performant. He builds and publishes Python libraries (attachments, functai, ovllm) that streamline LLM contexts and reproducible pipelines, drawing inspiration from ggplot2 and dplyr to improve AI ergonomics and API design. At Elsevier he led AI Factory and data platform migrations, delivering distributed pipelines and vLLM-backed batch inference that saved costs and scaled scientific analytics. Now at Synthetic Exploration he focuses on prompt optimization, RAG systems, and agentic protocols like MCP to push cutting-edge agent workflows into production. Beyond engineering, he co-founded a sustainable farm e-commerce venture and maintains a habit of creating practical developer tools on weekends, reflecting a maker mindset that bridges research, product, and real-world impact.
11 years of coding experience
5 years of employment as a software developer
Master of Science (M.Sc.), Biology, A+, Master of Science (M.Sc.), Biology, A+ at Université du Québec en Outaouais
Bachelor of Science (B.Sc.), Biologie, général, Bachelor of Science (B.Sc.), Biologie, général at University of Ottawa
Doctor of Philosophy - PhD, Ecology, Evolution, Systematics, and Population Biology, Doctor of Philosophy - PhD, Ecology, Evolution, Systematics, and Population Biology at McGill University
Contributions:10 commits, 10 pushes, 1 branch in 11 months
web-of-sciencegoalgraduatebeginningr-package
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