Summary
Daniel Vargas is a Senior Machine Learning Engineer based in Montreal with nine years of experience turning ML research into production-grade systems for startups and high-growth companies. He excels at defining technical strategy, managing engineering roadmaps, and guiding teams through the full lifecycle from architecture and R&D to scalable deployment. His background spans hands-on model development, AI implementation advising, and leadership roles including Director of AI Engineering, giving him a rare combination of technical depth and operational rigor. Daniel has repeatedly bridged complex ML capabilities to measurable business outcomes across domains from neuroscience to consumer fitness. He brings an engineering management master鈥檚 perspective to prioritize value-driven AI investment and has a track record of helping organizations identify where AI actually creates competitive advantage. Quietly data-focused and methodical, he often pairs Lean Six Sigma-informed process thinking with modern ML best practices to accelerate delivery.
9 years of coding experience
11 years of employment as a software developer
Johns Hopkins University
Nanodegree Machine Learning Engineer Machine Learning (Online), Nanodegree Machine Learning Engineer Machine Learning (Online) at Udacity
Bachelor of Engineering - BE Industrial Engineering, Bachelor of Engineering - BE Industrial Engineering at Instituto Tecnol贸gico de Santo Domingo
Master of Engineering (MEng) Engineering Management, Master of Engineering (MEng) Engineering Management at University of Ottawa
Spanish, French, English