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The Ops in MLOps - Process and People

Posted Feb 21, 2023 | Views 529
# MLOps perspective
# Customer Success
# Realistic Expectations
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SPEAKERS
Shalabh Chaudhri
Shalabh Chaudhri
Shalabh Chaudhri
Head of Customer Success @ Union AI

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 from B2B infrastructure and platform solutions.

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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 from B2B infrastructure and platform solutions.

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Demetrios Brinkmann
Demetrios Brinkmann
Demetrios Brinkmann
Chief Happiness Engineer @ MLOps Community

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.

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Abi Aryan
Abi Aryan
Abi Aryan
Machine Learning Engineer @ Independent Consultant

Abi is a machine learning engineer and an independent consultant with over 7 years of experience in the industry using ML research and adapting it to solve real-world engineering challenges for businesses for a wide range of companies ranging from e-commerce, insurance, education and media & entertainment where she is responsible for machine learning infrastructure design and model development, integration and deployment at scale for data analysis, computer vision, audio-speech synthesis as well as natural language processing. She is also currently writing and working in autonomous agents and evaluation frameworks for large language models as a researcher at Bolkay.

Prior to consulting, Abi was a visiting research scholar at UCLA working at the Cognitive Sciences Lab with Dr. Judea Pearl on developing intelligent agents and has authored research papers in AutoML and Reinforcement Learning (later accepted for poster presentation at AAAI 2020) and invited reviewer, area-chair and co-chair on multiple conferences including AABI 2023, PyData NYC ‘22, ACL ‘21, NeurIPS ‘18, PyData LA ‘18.

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Abi is a machine learning engineer and an independent consultant with over 7 years of experience in the industry using ML research and adapting it to solve real-world engineering challenges for businesses for a wide range of companies ranging from e-commerce, insurance, education and media & entertainment where she is responsible for machine learning infrastructure design and model development, integration and deployment at scale for data analysis, computer vision, audio-speech synthesis as well as natural language processing. She is also currently writing and working in autonomous agents and evaluation frameworks for large language models as a researcher at Bolkay.

Prior to consulting, Abi was a visiting research scholar at UCLA working at the Cognitive Sciences Lab with Dr. Judea Pearl on developing intelligent agents and has authored research papers in AutoML and Reinforcement Learning (later accepted for poster presentation at AAAI 2020) and invited reviewer, area-chair and co-chair on multiple conferences including AABI 2023, PyData NYC ‘22, ACL ‘21, NeurIPS ‘18, PyData LA ‘18.

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SUMMARY

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.

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