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Applied AI @ Google X | PhD Astrophysics
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Extensive experience building ML systems that learn faint signals from a sea of noise. Spent many years working with remote-sensing data in the space industry, as a tech lead and managing teams. Now I work on memory scaling harnesses for deep agents, applied to specialized knowledge work.
University of Florida
Doctor of Philosophy (PhD), Astronomy and Astrophysics
January 1, 2009 – January 1, 2014
Universidad de Sevilla
Bachelor of Science (BS), Theoretical and Mathematical Physics
January 1, 2003 – January 1, 2009
X, the moonshot factory
Staff Research Engineer
February 1, 2025 – Present
Mountain View, California, United States · On-site
Planet
ML Software Engineer
August 1, 2023 – February 1, 2025
Planet
Senior ML Engineering Manager
February 1, 2022 – July 1, 2023
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ML Engineering Manager
August 1, 2018 – March 1, 2022
Planet
Senior Machine Learning Engineer
April 1, 2017 – August 1, 2018
Capital One
Data Scientist
October 1, 2014 – March 1, 2017
San Francisco Bay Area
Insight Data Science
Fellow
June 1, 2014 – August 1, 2014
Palo Alto, CA
University of Florida
PhD - Astrophysics
August 1, 2009 – March 1, 2014
Geansolar
Co-founder of GeanSolar
January 1, 2004 – January 1, 2008
Chiclana, Spain
Cultural Fit Analysis
The candidate's diverse experience, ranging from a startup co-founder to a Staff Research Engineer at Google[x] and various ML roles at Planet, indicates a strong cultural fit for innovative and challenging environments. Their background in astrophysics and subsequent transition into applied ML demonstrates intellectual curiosity and a problem-solving mindset. The blend of individual contributor and leadership roles suggests flexibility and a collaborative approach, aligning well with dynamic team structures. The focus on impactful projects (e.g., fraud detection, environmental monitoring) suggests a drive for meaningful contributions.
Soft Skills & Operational Fit
The candidate's career progression from individual contributor to manager and back to a research engineer role suggests adaptability and a strong drive for technical depth. Experience in leading teams indicates leadership and collaboration skills. The co-founding of a startup demonstrates entrepreneurial spirit and business acumen. The transition from astrophysics to data science and then ML engineering shows a strong capacity for learning and applying complex concepts to real-world problems.