Position: MLOps Engineer
Category: Python
English level: upper
Years of experience: 5


From Jan 2022 till now
I'm working as MLOps Engineer and enable model deployment automation to production systems.

As a software engineer I am responsible for:
1. Code development, analysis and refactoring;
2. Writing test automation scripts;
3. Creating and mainting instances on AWS;
4. Communication product owner, data scientists
5. Developing CI/CD systems

Tools & Technologies:  Python, PostgreSQL, GitHub Actions, Docker, Docker compose, Terraform, Kubernetes, ArgoCD, AWS

From Dec 2020 to Jan 2022
I was involved in project Feature Store. Feature store aim is to solve the full set of data management problems encountered when building and operating operational ML application. With helps of feature store it is possible to:
Run data pipelines that transform raw data into feature values
Store and manage the feature data itself
Serve feature data consinstently for training and inference purposes
To store historical data for train and test models we used PostgreSQL and for real-time data we used Redis.

Tools & Technologies: Python, PostgreSQL, Redis, Docker, Github Actions, S3, AWS EC2

From Dec 2018 to Nov 2020
During that time, I was involved in a "Data Lake" project, where we use ETL process, quality checks and business metrics for data validation. 

As a software engineer I was responsible for:
1. Code development, analysis and refactoring;
2. Creation of an automate structure and the approach to write tests for the current project;
3. Writing test automation scripts;
4. Working and interacting in an Agile environment within the Scrum team;
5. Participating in meetings for setup process and requirements, proposing technical, business solution and functions that were implemented;

Tools & Technologies: Python, Exasol, Jenkins, Docker, Amazon S3, SFTP.

From Jul 2018 to Nov 2018
During that time, I was involved in R&D project where we developed a monitoring system for racing cars in which I used Python as a primary programming language and CISCO Kinetic EFM as Edge & Fog Processing Module. 

As a software engineer I was responsible for:
1. Design logic for CISCO Kinetic EFM;
2. Implementing MQTT broker, sensor simulators in Python;
3. Covering Python code with unit tests;
4. Database design and implementation in CISCO Kinetic EFM;
5. Estimation and prioritization of tasks;

Tools & Technologies: Python, CISCO Kinetic EFM, Xinabox, Flask, Google Cloud Platform, PostgreSQL, TensorFlow, Mosquitto, MQTT, DS Links.