Research and drive to production new features and solutions using cutting edge technologies, with emphasis on AI.

Leveraging ML to help organizations control their data without complex engineering.

Rigorous mentored theoretical study in Machine Learning, hands on mini-projects and a large Capstone Project as follows:

● Weather Forecaster trained on multiple years of historic hourly Weather data from multiple

locations

● Relies on multiple weather models that use different Algorithms such as Deep Learning and

Linear Regression. Models include chronological features from the geographic location where

weather is being forecast and geographic locations adjacent to it

● Provides a Web UI that shows both the forecast and model performance metrics

● Centred around a Data, Model and Deployment Pipeline to guarantee robustness and

repeatability

● Technologies: Python, TensorFlow, Keras, Scikit-Learn, Pandas, Docker and AWS

● Github: https://github.com/sergeypine/WeatherLearner

Worked on micro services and the User-facing Web application that together provide state of the art global Internet health monitoring. Here I expanded my scope from purely Backend to Full Stack development and had a lot of fun, working with diverse technologies and on functionality across our ecosystem. One of most rewarding parts was working with our excellent Product Management to translate Customer requirements to engineering work.

Grew my Cloud technology knowledge with Kubernetes, Mongo DB and Grafana/Prometheus; also (after holding out all this time) developed user facing functionality with Front End Java Script (with Vue). In addition to that, did some work on our Cloud Agent Virtual Appliance, thus reaching into every level of the product.

By the end of my journey with ThousandEyes, I can confidently say that I know all the pieces that it takes to build a good ecosystem of Cloud Services, as well as run it reliably and provide high quality monitoring and instrumentation for it.

Built critical cloud scalable services that leveraged various AWS components, with focus on streaming and data pipelines. Was the go to engineer in situations when questions arose or something went wrong.

In that process shone the light into the nooks and crannies of various aspects of AWS implementations, from behaviour at high loads to performance intricacies. Designed and provided multi-lingual client SDKs to facilitate access to these services by using a Java implementation as the shared engine and hosting it on an internal "server" which exposed multi-lingual stubs. Tackled several tricky distributed computing challenges.

One of the most rewarding parts of my Autodesk experience was helping our internal Customers with adapting, tuning and deep troubleshooting of the data streaming Cloud services which I played key part in developing. Due to the critical nature of the services we needed to avoid loss of data at all costs-- a task which, I'm proud to say, we succeeded in, while having overwhelmingly positive and constructive interactions with all the parties involved.