// Abstract

Shalabh talks through their newfound appreciation for the MLOps perspective from a customer success standpoint. Shalabh's emphasis on setting realistic expectations and ensuring the delivery of promised value adds is particularly valuable.    

Generally, this episode provides a unique and insightful perspective on MLOps from the lens of customer success.

// Bio

Shalabh has worked in the MLOps domain since 2020 at Algorithmia and Union AI. His experience spans startups and small and large public companies. He has 10+ years of experience in the design, delivery, adoption, and business value realization of B2B infrastructure and platform solutions.

// MLOps Jobs board  

https://mlops.pallet.xyz/jobs

// MLOps Swag/Merch

https://mlops-community.myshopify.com/

// Related Links

https://www.union.ai/

--------------- ✌️Connect With Us ✌️ -------------

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Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/

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Connect with Shalabh on LinkedIn: https://www.linkedin.com/in/shalabhchaudhri/

Timestamps:

[00:00] Shalabh's preferred coffee

[01:18] Takeaways

[02:57] Huge shout out to Union AI!

[03:46] Reviews

[05:26] Shalab's journey

[07:00] The people and process of MLOps

[10:25] Accuracy measures and Multiple Stakeholders

[13:01] UnionAI's success where others fall short

[14:45] Legacy equipment

[17:06] Legacy tools versus open source

[19:27] Cataloging solution

[22:51] Stakeholders and maturity levels

[24:26] People and Process in MLOps

[29:00] Collaboration for Machine Learning

[31:08] Overcoming challenges

[34:17] AI and leadership decision-making

[35:33] Legacy Companies and AI

[39:39] Common pitfalls  

[42:24] Neglecting ROI

[46:25] Speaking to each level

[49:50] Being realistic

[51:29] Becoming a champion

[53:08] Transitioning to machine learning

[55:25] Customer's Skill and Success needed in ML  

[57:46] Different sizes of companies