Machine Learning 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
Flask-Redis-Websocket
January 30, 2019 – January 30, 2019
Flask Server that counts number of active request and display live data on webpage using websocket.
View ProjectModelPredictiveController
November 30, 2018 – November 30, 2018
ModelPredictiveController — GitHub repository
View ProjectTrafficSignClassifier
November 30, 2018 – November 30, 2018
TrafficSignClassifier — GitHub repository
View ProjectVehicleDetection
November 29, 2018 – November 30, 2018
VehicleDetection — GitHub repository
View ProjectDeepLearningBehaviourCloning
November 29, 2018 – November 29, 2018
DeepLearningBehaviourCloning — GitHub repository
View ProjectUnscentedKalmanFilter
November 29, 2018 – November 29, 2018
UnscentedKalmanFilter — GitHub repository
View ProjectAdavanceLaneLineDetection
November 29, 2018 – November 29, 2018
AdavanceLaneLineDetection — GitHub repository
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and focus on specific technical challenges in robotics, control systems, and computer vision. While this shows initiative, the lack of team projects or diverse application areas makes it difficult to assess cultural fit or collaboration potential. The projects align somewhat with a Data Scientist role, particularly those involving machine learning, but the breadth of data science applications (e.g., statistical modeling, A/B testing, data engineering) is not evident.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric or English test scores are available, and project descriptions are very brief.