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Why is MLOps Hard in an Enterprise? // Maria Vechtomova & Basak Eskili // MLOps Podcast #159

Why is MLOps Hard in an Enterprise? // Maria Vechtomova & Basak Eskili // MLOps Podcast #159

FromMLOps.community


Why is MLOps Hard in an Enterprise? // Maria Vechtomova & Basak Eskili // MLOps Podcast #159

FromMLOps.community

ratings:
Length:
55 minutes
Released:
May 30, 2023
Format:
Podcast episode

Description


MLOps Coffee Sessions #159 with Maria Vechtomova, Lead ML engineer, and Basak Eskili Machine Learning Engineer, at Ahold Delhaize, Why is MLOps Hard in an Enterprise? co-hosted by Abi Aryan.

// Abstract
MLOps is particularly challenging to implement in enterprise organizations due to the complexity of the data ecosystem, the need for collaboration across multiple teams, and the lack of standardization in ML tooling and infrastructure. In addition to these challenges, at Ahold Delhaize, there is a requirement for the reusability of models as our brands seek to have similar data science products, such as personalized offers, demand forecasts, and cross-sell.

// Bio
Maria Vechtomova
Maria is a Machine Learning Engineer at Ahold Delhaize. Maria is bridging the gap between data scientists infra and IT teams at different brands and focuses on standardization of machine learning operations across all the brands within Ahold Delhaize.

During nine years in Data&Analytics, Maria tried herself in different roles, from data scientist to machine learning engineer, was part of teams in various domains, and has built broad knowledge. Maria believes that a model only starts living when it is in production. For this reason, last six years, her focus was on the automation and standardization of processes related to machine learning.

Basak Eskili
Basak Eskili is a Machine Learning Engineer at Ahold Delhaize. She is working on creating new tools and infrastructure that enable data scientists to quickly operationalise algorithms. She is bridging the space between data scientists and platform engineers while improving the way of working in accordance with MLOps principles.

In her previous role, she was responsible for bringing models to production. She focused on NLP projects and building data processing pipelines. Basak also implemented new solutions by using cloud services for existing applications and databases to improve time and efficiency.

// MLOps Jobs board
https://mlops.pallet.xyz/jobs

// MLOps Swag/Merch
https://mlops-community.myshopify.com/

// Related Links
MLOps Maturity Assessment Blog: https://mlops.community/mlops-maturity-assessment/
The Minimum Set of Must-Haves for MLOps Blog: https://mlops.community/the-minimum-set-of-must-haves-for-mlops/
Traceability & Reproducibility Blog: https://mlops.community/traceability-reproducibility/

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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
Connect with Abi on LinkedIn: https://www.linkedin.com/in/goabiaryan/
Connect with Maria on LinkedIn: https://www.linkedin.com/in/maria-vechtomova/Connect with Basak on LinkedIn: https://www.linkedin.com/in/ba%C5%9Fak-tu%C4%9F%C3%A7e-eskili-61511b58/
Released:
May 30, 2023
Format:
Podcast episode

Titles in the series (100)

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.