Sasha Jaksic

Sasha Jaksic has a diverse and extensive work experience in software engineering and machine learning. Starting in 2004, Sasha worked as a Software Engineering Intern at MDL Information Systems. In 2005, Sasha joined CNET networks as a Software Engineer, where they designed and built a web crawler and REST client for fetching consumer opinions and product reviews.

In 2006, Sasha became a Senior Programmer at Gymboree Inc., leading the integration between their shipping system and DHL Global Mail system. They also extended the web content management system to use Scene7 for image hosting.

From 2008 to 2009, Sasha worked as a Senior Software Engineer at Yodlee, designing and developing features for their BillPay system.

Sasha then became an Independent Consultant from 2009 to 2011, where they extended a proprietary object-relational persistence system and created multi-dimensional aggregation reports for Yapstone Inc.

In 2011, Sasha joined YapStone Inc. as a Senior Software Engineer, where they designed and implemented a data integration system and optimized payment processing components.

Starting in 2016, Sasha worked at Training for Autonomous Vehicle Engineering as a Machine Learning Engineer, focusing on deep learning projects, computer vision projects, and robotics projects.

From 2019 to 2020, Sasha worked at Udacity as a Mentor for C++ and Self-Driving Car Engineering nanodegrees.

Currently, Sasha is working at Clostra, Inc. as a Machine Learning Engineer.

Sasha Jaksic earned a Master's degree in Computer Science from San Francisco State University between 2002 and 2005. Later, in 2017, Sasha pursued a Self-Driving Car Engineer degree in Mechatronics, Robotics, and Automation Engineering from Udacity. Sasha also obtained a Data Science Certificate from Microsoft in February 2017. Additionally, Sasha has multiple edX Verified Certificates in various subjects such as Applied Machine Learning, Data Science Essentials, Data Science Professional Project, Principles of Machine Learning, and Statistical Thinking for Data Science and Analytics.