Position: Machine Learning Engineer
Category: Data Science
English level: fluent
Years of experience: 1

1st place in Winter Science Fair, Project: Autonomous Plant Watering system controlled by android (team member). 

2nd place in CanSat Azerbaijan 2019 (Team member)

Computer vision based accomplishments
30% increase in Big Rock (minority) class of AI4Mars Segmentation dataset.

Created powerful Novel Unsupervised Domain Adaptation method to decrease domain gap between sythetic and real dataset.
04/2022 - present
Intern Deep Learning Engineer 
•	Achieved superior result on Semantic Segmentation by applying state of art models and mathematical solutions to overcome challenges of the dataset by improving 30% accuracy on minority class on Convolutional Neural Networks (CNN). 
•	Made research about domain adaptation methods and created novel 3-stage unsupervised domain adaptation mechanism on multi-task learning model. Increased feature extraction capability by using unsupervised learning and self-training over 40%.
•	Increased robustness of the model by 10% with transformer-based architecture

07/2019 – 09/2019
Intern Instrumentation and Control Engineer
•Contributed for factory acceptance test by creating simulation software in C# for safe gas release scheme.
•Corrected mismatching between actual devices in platforms and obsolescence database.

02/2018 – 08/2018
Firmware Developer
•Optimized latency of raspberry by applying firmware corrections (Python) and OS modifications (Linux)
•Created sensor-motor architecture to test designs of mechanical engineers

Additionally from next semester, i am instructor for "AI and ML Fundamentals" course in university in Azerbaijan.
My expectation is to have friendly environment and efficient use of tools to eliminate disadvantages of remote work such as documentation board, agile working and platform for communication. 
Additional technical expectation is cloud access to GPUs