Machine Learning Engineer Intern Resume
Newport Beach, CA
TECHNICAL SKILLS
Programming Languages and Databases: Python, SQL, Presto, PySpark, Hadoop, Hive familiar with Scala, Spark
Deep Learning Libraries: TensorFlow, Keras, Caffe, Nvidia - Digits
Machine learning Libraries: Scikit-Learn, NumPy, Pandas, Matplotlib, CNN, RNN, LSTM, GRU, Autoencoder, Logistic Regression, Decision Tree, Random Forest, SVM, Ensemble learning, Unsupervised learning, N atural language processing (NLP), Computer Vision, Recommendation Systems
Cloud: Microsoft Azure cloud computing service
Data visualization: Tableau, Incorta
Pipeline construction: Airflow , Azure DevOps, Docker
Agile and Version Control: Git, Bitbucket, Jira, Wiki
Management Experience : Supervisor assistant, Team Leader, and Coordinator
Coursework Focus: Machine Learning, Neural Network, Deep Learning, Software Engineering
PROFESSIONAL EXPERIENCE
Machine Learning Engineer Intern
Confidential - Newport Beach, CA
Responsibilities:
- Researching and experimenting state of the art machine learning and deep neural networks techniques for time series to predict future moves in the financial markets
Machine Learning Research Assistant
Confidential
Responsibilities:
- Researching and experimenting state of the art deep neural networks architectures for images and temporal action recognition in videos.
Software Engineer (IT Coordinator/IT Apps Project Team Leader)
Confidential
Responsibilities:
- Planned, supervised and coordinated implemented and maintained Maximo system, PI System, salary system, Sakhr (server-based translation system), which created the company application infrastructure and reduced the operation cost
Software Engineer
Confidential
Responsibilities:
- Planned, supervised and coordinated building and equipping several server rooms, security and communication systems in Confidential company, which created the company infrastructure and reduced the operation cost
Software Engineer
Confidential
Responsibilities:
- Maintained the company computers and the salary system for the civil engineer department