
Principal AI Engineer at Cisco | Kaggle Master (Top 1%)
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Eric's accomplishments include pioneering early AI features in Webex, establishing an AI training program at Cisco, attaining Master status at Kaggle, serving as a committee member at IEEE BigData, ICC, and Globecom, and as a Senior Member at IEEE. Furthermore, Eric is credited with inventing more than 30 patents.
McGill University
M.B.A., International Business
N/A – Present
The University of Tokyo
Ph.D., Computer Science
N/A – Present
McGill University
B.Sc., Computer Science
N/A – Present
Cisco Systems
Principal Engineer in ML/AI, CTO Office, Collaboration and Security
January 1, 2016 – Present
Orange County, California Area
Kaggle
Kaggle Master (Top 1%)
January 1, 2015 – Present
NTT Innovation Institute, Inc.
Chief Data Scientist
January 1, 2012 – January 1, 2016
Palo Alto
NTT R&D
Senior Research Scientist (主任研究員)
January 1, 2001 – January 1, 2012
Tokyo, Japan
Cloudera Certified Professional: Data Scientist
Cloudera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily focused on Machine Learning and AI, with a strong emphasis on research and development. While they have applied ML to security problems (DDoS, SIP flooding), their primary expertise is not directly in core security engineering domains like incident response, vulnerability management, or security architecture. Their experience in a large corporate environment (Cisco, NTT) suggests an ability to work within established structures. The Kaggle participation indicates a drive for continuous learning and competitive spirit. However, the direct alignment with a 'Security Engineer' role, which typically requires a broader and deeper security-specific skill set beyond ML applications, is moderate. The candidate's profile leans more towards an 'AI/ML Security Researcher' or 'MLSecOps Engineer' rather than a general 'Security Engineer'.
Soft Skills & Operational Fit
The candidate's extensive experience in leading ML/AI initiatives, developing MLaaS platforms, and participating in high-level competitions suggests strong problem-solving, innovation, and self-driven learning abilities. Their role in the CTO Office and creating training programs indicates leadership and mentorship potential. However, specific soft skills like teamwork, communication style, and adaptability cannot be fully assessed without interview data.