Loic Dagnas
Backend EngineerAI Engineer
Sinequa
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Ecole normale supérieure
Master MVA, Machine Learning and Computer Vision
January 1, 2015 – January 1, 2016
Ecole nationale des Ponts et Chaussées
Engineer's degree, Mathematical engineering and Computer Science
January 1, 2012 – January 1, 2016
Stanislas (Paris)
Preparatory Classes, MPSI-MP, Mathématiques Physique
January 1, 2010 – January 1, 2012
Lycée saint Paul Angoulême
Baccalauréat, Scientifique
January 1, 2007 – January 1, 2010
Sinequa
Machine Learning Team Manager
December 1, 2020 – February 1, 2026
Sinequa
Machine Learning Architect
March 1, 2020 – February 1, 2026
Sinequa
R&D Engineer - Machine Learning
December 1, 2016 – March 1, 2020
Sinequa
R&D intern - Machine Learning
April 1, 2016 – September 1, 2016
Greater Paris Metropolitan Region
Inria
Applied Mathematics research intern
January 1, 2015 – June 1, 2015
Chile
Dassault Systèmes
Applied mathematics engineer intern
July 1, 2014 – December 1, 2014
Greater Paris Metropolitan Region
GéoPonts
March 1, 2015 – Present
Geolocalized job search and alumni platform. We built a map of jobs and internships for our University's students and alumni. We help strengthen the bond and network between generations. We provide customized and context-aware emails for professionals and job-seekers with our data-mining bot, Alfred.
Cultural Fit Analysis
The candidate has a strong background in Machine Learning and R&D, which might align with an innovative and research-driven culture. However, the target role is 'Backend Engineer', which is a significant shift from their primary ML focus. While ML often involves backend components, the resume does not explicitly detail backend engineering experience (e.g., distributed systems, API design, database management beyond ML data pipelines). The single personal project 'GéoPonts' is vaguely described without specific technologies, making it hard to assess broader technical interests or collaborative project experience. This lack of explicit backend engineering experience and project diversity suggests a moderate cultural fit challenge for a pure backend role.
Soft Skills & Operational Fit
The candidate's career progression to Machine Learning Team Manager suggests leadership, project management, and potentially strong communication skills within a technical context. However, without specific project details or behavioral assessment data, it's difficult to fully assess operational fit beyond their technical leadership capacity.