Marcos Nieves is a results-driven small business owner and bilingual professional with nine years of experience blending customer-focused roles and technical contributions. He has led an e-commerce venture since 2019 while also serving as a Real Estate Advisor and previously executing FEMA housing inspections under tight compliance deadlines. Skilled in team leadership, conflict resolution, and strategic planning, Marcos brings a customer-first mindset from roles in health and wellness sales to disaster-relief operations. He has practical machine learning engineering experience contributing operators and tests to the Java deep learning framework DJL, demonstrating hands-on coding and open-source collaboration beyond his client-facing work. Based in Florida and fluent in Spanish and English, he excels at translating technical fixes and regulatory requirements into clear, actionable outcomes for stakeholders. Open to partnerships, he combines entrepreneurial grit with a track record of shipping tangible results across diverse environments.
9 years of coding experience
Bachelor's degree, Labors Relations, Bachelor's degree, Labors Relations at University of Puerto Rico-Rio Piedras
An Engine-Agnostic Deep Learning Framework in Java
Role in this project:
ML Engineer
Contributions:12 reviews, 9 commits, 9 PRs in 3 months
Contributions summary:Marcos primarily contributed to the development of the DJL framework by implementing new operators, fixing bugs, and expanding existing functionalities related to NDArrays. Their work includes adding the `norm` and `oneHot` operators and fixing a `sequenceMask` error. The user also refactored and added unit tests for the implemented operators, showcasing their understanding of the framework's core components and testing procedures.
Contributions:7 commits, 6 pushes, 1 branch in 1 year 8 months
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