Mlops Engineer

12/2022 – 12/2023

Developing and setting up feature store for real-time ml applications and model retraining processes using feast , azure data bricks and azure elastic cache

Development of ML servers in Kubernetes using seldon-core

Development of serverless and event driven setup for real time ML model monitoring and alerting with seldon , Knative, Azure eventhubs, prometheus, opensearch and Grafana.

Setting up Self hosted Github actions in Azure AKS for GitHub enterprise for different CI/CD applications

Implemented Central Cloud Monitoring system using grafana and azure monitor for different teams across the group

Championing the usage of best deployment practices using terraform with Atlantis within the team.

Automation of various data bricks deployment process using GitHub actions

Development of Kubeflow pipelines for various use cases.

Data Science

8/2020 – 9/2021

Development and maintenance of data pipelines over a tech stack comprising of Snowflake, hevo, dbt and looker.
• Creating of Embedded dashboards Which is integrated in Plentific’s main app as a service to Plentific’s main app
• Development and maintenance of Automated website scraping system using slackify (slack bot), airflow and scrapy.
• Support Business development teams for creating their own custom dashboards in looker
• Data manipulation and Development of looker components using Lookml and dbt.
• Scrape websites for business development team using python libraries like scrapy and beautifulsoup.
• Development of Looker dashboards for multiple teams across Plentific.
Design, Development and Maintenance of machine learning ecosystem in AWS using Kubeflow and Sagemaker.
• Master thesis on Hybrid recommendation System For short lived items For Plentific’s Marketplace.

Data Science, Maschinelles Lernen

12/2019 – 12/2021

• Design, Development and maintenance of Microservices based infrastructure in AWS for 3 microservices with 99% Uptime from scratch.
• Development of CI/CD pipelines for automated deployment of microservices in different environments using Jenkins, Github actions and ArgoCD in AWS.
• Development of Restful API using Fastapi with multiple endpoints with Oauth authentication system.
• Development and maintenance of ETL pipelines Using Airflow
• Development of Machine Learning Model for German real estate price prediction using regression algorithms.
• Design, development and maintenance of end-to-end machine learning eco system using Kubeflow, Mlflow, Jenkins-x and Seldon core
• Development of Automated Chatops based CI/CD system for Machine learning models in different environments using Jenkins-x, Argocd and Mlflow.
• Development of End-to-End machine learning pipelines for training, tuning, testing, and deployment in AWS with 99% uptime.
• Championing the introduction and use of best machine learning practices within the team at different levels/tools

Data Science, Maschinelles Lernen