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Deep learning / ML / AI at Roblox | PhD
Machine learning and robotic engineer with 15+ years of experience focused on the algorithmic aspects. Strong experience in distributed systems and coordination of multiple agents. Machine learning applied to perception and to the control of mobile robots. Experience with multiple robotic platforms: from tiny mobile robots to autonomous trucks. Published 20+ peer-reviewed conference articles and ten journal articles, most as the first author. Work well independently, as well as part of a team. Spanish nationality. Swiss residence permit.
EPFL
Doctor of Philosophy - PhD, Distributed Robotics
January 1, 2006 – January 1, 2007
Universidad Politécnica de Madrid
Doctor of Philosophy (PhD), Robotics and Automation Engineering
January 1, 2005 – January 1, 2010
The Faculty of Engineering at Lund University
Master of Science (MSc), Engineering
January 1, 2003 – January 1, 2004
Universidad Politécnica de Madrid
Master of Science (MSc), Telecommunications Engineering
January 1, 1998 – January 1, 2004
Roblox
Principal Software Engineer
October 1, 2023 – Present
Roblox
Senior Software Engineer
January 1, 2021 – September 1, 2023
Loom.ai
Deep Learning Engineer
November 1, 2018 – December 1, 2020
Advertima
Machine Learning Engineer
July 1, 2017 – October 1, 2018
St Gallen
EPFL (École polytechnique fédérale de Lausanne)
Postdoctoral Researcher in Distributed Robotics and Machine Learning
February 1, 2013 – December 1, 2015
Lausanne Area, Switzerland
Robolabo
Postdoctoral Researcher in Robotics
January 1, 2012 – January 1, 2013
Universidad Politecnica de Madrid
EPFL
Visiting Researcher
October 1, 2006 – March 1, 2007
Lausanne Area, Switzerland
Universidad Politécnica de Madrid
Researcher in Distributed Robotics
January 1, 2005 – December 1, 2010
RBZ Robot Design
Engineer and Co-founder
December 1, 2003 – June 1, 2005
Madrid Area, Spain
Collaborative Sensing and Decision Making for Intelligent Vehicle Maneuvers
September 1, 2014 – January 1, 2015
New generations of intelligent vehicles are becoming more and more developed. These kind of vehicles have very powerful resources inside, such as efficient computers, sensors and actuators. These cars can be extended on many ways such that they can reduce a lot the injuries caused by the road accidents. One of the most dangerous maneuver on the road is the overtaking. This project deals with the implementation of collaborative sensing and decision making in this specific scenario. At the beginning of the project, two path-following controllers have been implemented. It is an efficient way to control the vehicles on the track with predefined trajectories. Then, a lane detection algorithm has been implemented using the information received from the Lidars. This algorithm tries to place the vehicles seen by the Lidars on the right lane. Finally, a decision making algorithm has been implemented. This algorithm is used with a Finite State Machine in order to have a realistic behavior.
Solar Deacthlon Europe 2012 - Monitoring
March 1, 2011 – Present
Solar Decathlon Europe 12 is an international competition created through an agreement signed between the Ministry of Housing of the Government of Spain and the United States Government, co-organized by Universidad Politécnica de Madrid in which universities from all over the world meet to design, build and operate an energetically self-sufficient house, grid-connected, using solar energy as the only energy source and equipped with all of the technologies that permit maximum energy efficiency. Robolabo took over the task of designing, implementing and installing the monitoring system in charge of logging these variables, process them and show them in the monitoring web of the competition.
telc Deutsch B2
telc GmbH - The European Language Certificates
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background spans academic research, startups (RBZ Robot Design, Loom.ai, Advertima), and large tech companies (Roblox), indicating adaptability to diverse work environments. Their involvement in international projects (Solar Decathlon Europe, EPFL) and multiple PhDs suggests a strong drive for continuous learning and intellectual curiosity. The transition from robotics research to deep learning and software engineering roles shows a willingness to evolve and apply skills across different domains. The target role of ML Engineer aligns well with their recent industry experience.
Soft Skills & Operational Fit
The candidate's experience as a Postdoctoral Researcher and teaching assistant suggests strong collaboration, mentorship, and communication skills. Their involvement in coordinating projects and supervising students indicates leadership potential and organizational abilities. The co-founding experience also points to an entrepreneurial mindset and problem-solving skills. The long tenure at Roblox (Senior to Principal Software Engineer) indicates stability and growth within an organization.