AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Lead Machine Learning Engineer, Search/NLP
I am a Machine Learning Engineer specializing in Natural Language Processing and Deep Learning, currently working with the Search and Sensei teams at Adobe. My work focuses on architecting and implementing cutting-edge solutions to enhance product search capabilities and creative intelligence features. Before Adobe I worked as an Applied Scientist at Amazon's Alexa Science team where I developed dialogue management systems to improve conversational AI interactions. I hold a PhD in Computer Science from Drexel University, where I conducted research under Dr. Santiago Ontañón Villar and Dr. Jichen Zhu, focusing on Artificial Intelligence applications in digital entertainment. I am interested in topics related to Machine Learning, Natural Language Understanding and Natural Language Generation, User/player Modeling and Intent/goal understanding. My past experience includes: Fundamental and applied research. Entrepreneurship. Software development, project management and team leadership. I have professional experience in: Machine learning and software development in Python and Java. Distributed and large-scale data analysis and ETL workflows with PySpark. Relational databases (PostgreSQL...), non-relational databases (DynamoDB...), graph databases (Neo4j) and indexing services (Elasticsearch, Solr/Lucene). Customization and deployment of desktop, cloud, and web based applications, and distributed APIs/microservices architectures. Additionally, I have research experience in: Natural Language Processing, Information Extraction, Machine Learning and Commonsense reasoning. User research and player modeling in digital entertainment applications. I am also familiar with cloud computing infrastructure and management of serverless environments (AWS, Google Cloud).
Drexel University
Doctor of Philosophy (PhD), Artificial Intelligence
January 1, 2012 – January 1, 2017
Universitat Autònoma de Barcelona
M.S., Artificial Intelligence
January 1, 2009 – January 1, 2010
University of California, Santa Cruz
Information Systems and Technology Management
January 1, 2007 – January 1, 2008
Universitat Autònoma de Barcelona
Bachelor’s Degree, Computer Science
January 1, 2006 – January 1, 2009
Adobe
Lead Machine Learning Engineer
July 1, 2024 – Present
Adobe
Senior Machine Learning Engineer, Search/NLP
July 1, 2021 – July 1, 2024
Amazon
Machine Learning/Applied Scientist - Alexa Science Team
December 1, 2017 – June 1, 2021
Greater Boston
Amazon
Machine Learning/Applied Scientist Intern - Alexa Science Team
June 1, 2016 – September 1, 2016
Greater Boston
Drexel University
Research Assistant
September 1, 2012 – December 1, 2017
Greater Philadelphia
SNTalent (Referup S.L.)
Co-Founder, Lead developer, Software architecture consultant
July 1, 2009 – January 1, 2013
Greater Barcelona Metropolitan Area
CreateSpace
Software Development Intern
November 1, 2008 – July 1, 2009
Santa Cruz, California
Pingsta
Software Development Intern
September 1, 2008 – November 1, 2008
San Francisco Bay Area
Tiktala
Software Development Intern
September 1, 2008 – November 1, 2008
San Francisco Bay Area
Doom Informàtica
Software Developer
March 1, 2001 – December 1, 2006
Terrassa, Spain
Cultural Fit Analysis
The candidate's background includes significant tenure at large, innovative tech companies (Amazon, Adobe) and academic research, indicating adaptability to diverse work environments. The co-founder experience also suggests initiative and a results-oriented mindset. The target role of NLP Engineer aligns perfectly with their academic specialization and professional experience, particularly in search and Alexa science.
Soft Skills & Operational Fit
The candidate's career progression from individual contributor to lead roles, coupled with co-founder experience, suggests strong leadership, problem-solving, and project management skills. The lack of detailed project descriptions limits the ability to fully assess communication and collaboration styles, but the roles themselves imply a high degree of operational fit for senior technical positions.