Claudiu Musat
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
Research Manager at Google DeepMind
Machine Learning Leader with 20+ years of experience leading research and development teams, building impactful models and products, and fostering innovation in academia and industry. Proven ability to set strategic direction, scale teams, and deliver results that enhance user experience and drive business growth. Extensive expertise in multimodal interactions, recommender systems, sentiment analysis, and MLOps. Passionate about talent development and knowledge sharing. I guide the research agenda and Machine Learning development for stylus perception at Google DeepMind. I more than doubled our team, reshaped the Google student interaction model and increased internal collaboration and product alignment. Before Google, I created the Swisscom AI research and ML Flywheel teams from zero, hired 70+ data scientists and students, published in top conferences and managed the relationship with academic partners. I built and scaled up research-minded engineering and data science teams.
University POLITEHNICA of Bucharest
Ph.D., Computer Science
January 1, 2008 – January 1, 2011
University POLITEHNICA of Bucharest
Bachelor, Computer Science
January 1, 2002 – January 1, 2007
Lucerne University of Applied Sciences and Arts
Lecturer
September 1, 2024 – Present
Lucerne, Switzerland
Google DeepMind
Research Manager
May 1, 2024 – Present
Zurich, Switzerland · Remote
Research Manager
September 1, 2021 – May 1, 2024
Switzerland
Swisscom
Machine Learning Manager
October 1, 2020 – September 1, 2021
Swisscom
Director of Research for Data, Analytics & AI
June 1, 2018 – September 1, 2021
Swisscom
Research Director, Artificial Intelligence & Machine Learning Group
September 1, 2016 – June 1, 2018
Swisscom
Senior Data Scientist, Artificial Intelligence & Machine Learning Group
April 1, 2016 – August 1, 2016
dMetrics
Senior Researcher
November 1, 2015 – March 1, 2016
ObViz
Founder
October 1, 2014 – November 1, 2015
Lausanne
EPFL
Research Associate
November 1, 2011 – October 1, 2014
Lausanne Area, Switzerland
Bitdefender
Researcher
January 1, 2006 – November 1, 2011
Bucharest, Romania
Bitdefender
Developer
January 1, 2004 – January 1, 2006
Bucharest, Romania
Perspectives
February 1, 2014 – Present
Keywords: topic modeling, opinion mining, natural language processing Technologies: Java, Android, Python, MySQL Android application that crawls the latest news articles for several subjects, analyses them and automatically splits them into topics for each subject. Each news article within a topic will be assigned an opinion polarity regarding that topic. The app will then display an equal number of positive and negative news regarding each topic so that the reader can quickly get an idea of the latest events and their impact. Developed within the AI Lab at EPFL.
Cultural Fit Analysis
The candidate's diverse experience across academia, startups, and large corporations (Google, Swisscom) suggests adaptability and a broad perspective. Their involvement in teaching and mentoring, coupled with leading research initiatives, indicates a collaborative and knowledge-sharing mindset. The focus on innovation, evidenced by patents and startup success, aligns with a culture that values pioneering solutions. The breadth of projects from customer understanding to digital assistants shows a versatile approach to applying ML, fitting well into dynamic environments.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership, strategic planning, and team-building skills through their various management roles. Their experience in coordinating academic partnerships and guiding students indicates mentorship and collaboration abilities. Entrepreneurial experience as a founder also suggests initiative and problem-solving. The descriptions highlight a focus on practical application of research and scaling data science teams, indicating a strong operational fit for driving ML initiatives.