Clemente Cuevas
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Forward Deployed AI Engineer at Tribe
Hello, I'm Clemente. I've been building AI and ML systems for over a decade, from the word2vec days through today. One really powerful motivation I've consistently found across my career has been to share and build tools I've found genuinely transformative with other people across industries and roles and see what they do with them. My work has consistently been focused on applying powerful, modern AI models to solving complex business problems. In the past that involved a lot of work around search, NLP, applied ML on large datasets, and data engineering. Lately I've spent a lot more time thinking about how to build distributed systems with agents, and how to accelerate the software development lifecycle and manage complicated systems leveraging modern AI tooling. Within engineering, I have specific interests in causal reasoning, the intersection of design and engineering, and a particular interest in the evolution and propagation of open source software and their associated philosophies (things like the UNIX philosophy, and the rise of Rust). Some of my personal interests are music, games (in the abstract and in the specific), and food.
University of Florida
Bachelor of Science, Physics/Mathematics
January 1, 2010 – January 1, 2014
Tribe AI
Forward Deployed AI Engineer
March 1, 2026 – Present
Los Angeles Metropolitan Area · Remote
Pryon
Senior Machine Learning Engineer
November 1, 2023 – March 1, 2026
Raleigh, North Carolina, United States · Remote
Bounti Labs
Senior Machine Learning Engineer
December 1, 2022 – December 1, 2023
Los Angeles Metropolitan Area · Remote
Interos Inc
Senior Machine Learning Engineer
November 1, 2020 – January 1, 2023
Remote
Element AI
Applied Research Scientist / ML Engineer
September 1, 2018 – April 1, 2020
Montreal, Canada Area
EruditeAI
Lead AI Engineer
February 1, 2017 – September 1, 2018
Greater Montreal Metropolitan Area
Enigma.io
Data Scientist / ML Engineer
December 1, 2014 – February 1, 2017
New York City Metropolitan Area
Canopy Apps
Search Consultant
September 1, 2014 – September 1, 2014
New York City Metropolitan Area
SFX
Data Scientist
May 1, 2014 – November 1, 2014
New York, NY
University of Rochester
Research Assistant
May 1, 2013 – August 1, 2013
Rochester, NY
University of Florida
Research Assistant
May 1, 2011 – May 1, 2014
University of Florida
Dynamic Music Festivals
Sound Technician
August 1, 2007 – May 1, 2010
Orlando, Florida
Papers We Love
December 1, 2014 – Present
Papers We Love is a project spanning multiple chapters around the world committed to helping unite the communities of Academia and Industry around the theme of sharing research and insight across domains and boundaries. I was a co-organizer for the NYC Papers We Love Chapter and assist with analytics and other technical matters.
Claude Certified Architect - Foundations
Anthropic
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's career trajectory shows a consistent focus on AI and Machine Learning, indicating strong alignment with an ML Engineer role. The diversity of projects, from knowledge graphs and LLMs to supply chain analytics and quantum optical phenomena, suggests a broad intellectual curiosity and adaptability. The 'Papers We Love' involvement indicates a community-oriented and continuous learning mindset. However, the lack of specific details on team collaboration or work style in the provided descriptions makes a deeper cultural fit assessment challenging.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight leadership in development and implementation, suggesting strong initiative and project ownership. The reduction in QA incident rates by 75% indicates a focus on quality and process improvement. Participation in 'Papers We Love' suggests a collaborative and knowledge-sharing mindset. However, without direct assessment data, specific soft skills like stress handling or team collaboration cannot be definitively evaluated.