Zha Chenyu
AI EngineerR&D Machine Learning Enginner
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
R&D Machine Learning Enginner
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Working in intelligence artificielle domain since 2017, Experiences in AI through diverse projects/models: - Classification task using CNN - Object Detection such as MaskRCNN(Segmentation semantic or instance ) - Edge Detection network (RCF) - GAN(pix2pixHD, cycleGAN) - Pose estimation 2D using KeyPoint detector - Video interpolation network through optical flow - Tree algorithm (xgboost, adaboost) - Mobile framework (deepLab, tensorflow lite, yolo) Framework: torch, tensorflow Deploying AI models using Nvidia triton inference server.
Université Paris Cité
Master 2 (M2), Mathématiques appliquées aux traitement d'images
January 1, 2015 – January 1, 2016
Dental Monitoring
R&D AI Enginner
May 1, 2017 – Present
巴黎地区
CNRS - Centre national de la recherche scientifique
Chercheur en apprentissage machine
May 1, 2016 – January 1, 2017
Île-de-France, France
École normale supérieure
Chercheur en laboratoire
May 1, 2015 – October 1, 2015
Ville de Paris, Île-de-France, France
CEA
Projet de recherche
October 1, 2014 – November 1, 2014
Île-de-France, France
Cultural Fit Analysis
The candidate has a strong academic and research background, which aligns well with an R&D-focused AI Engineer role. However, the project diversity is limited to academic and research internships, with only one long-term industry role. There is no information on personal projects or contributions outside of formal employment/education, which limits the assessment of broader interests or adaptability to different work environments. The experience is heavily concentrated in image processing and machine learning, which is a good fit for the target role, but lacks breadth in other AI domains or general software engineering practices.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The resume primarily details technical roles and responsibilities without explicit mention of collaboration, leadership, or problem-solving approaches in a team setting.