web02.fireside.fm Thu, 30 Apr 2026 08:16:46 -0500 Fireside (https://fireside.fm) Pipeline Conversations - Episodes Tagged with “Scale” https://podcast.zenml.io/tags/scale Thu, 27 Oct 2022 07:00:00 +0200 Pipeline Conversations brings you interviews with platform engineers, ML practitioners, and technical leaders building production AI systems. We dig into the real challenges of MLOps and LLMOps: orchestrating complex workflows on Kubernetes, fine-tuning and evaluating models at scale, and shipping AI that actually works. From ZenML. en-us episodic MLOps and LLMOps, from the trenches ZenML GmbH Pipeline Conversations brings you interviews with platform engineers, ML practitioners, and technical leaders building production AI systems. We dig into the real challenges of MLOps and LLMOps: orchestrating complex workflows on Kubernetes, fine-tuning and evaluating models at scale, and shipping AI that actually works. From ZenML. no machine-learning, machinelearning, mlops, deeplearning, ai, artificialintelligence, artificial-intelligence, technology, tech, mlops, llmops ZenML GmbH podcast@zenml.io Questioning MLOps with Lak Lakshmanan https://podcast.zenml.io/lak-lakshmanan 253cd080-cfca-4b29-9a53-1641ec9b384b Thu, 27 Oct 2022 07:00:00 +0200 ZenML GmbH full 2 ZenML GmbH This week I spoke with Lak Lakhshmanan, who worked for years at Google on ML and AI projects and products at a senior level and he also brings years of experience working on meteorology and other scientific projects previously. 53:02 no This week I spoke with Lak Lakhshmanan, who worked for years at Google on ML and AI projects and products at a senior level and he also brings years of experience working on meteorology and other scientific projects previously. Lak brings a ton of experience to the table and it was interesting to hear his suggestions around when it is and isn't appropriate to bring the full set of MLOps tools to the table, for example. We also discussed the fundamentals of doing ML-backed projects as well as the teams needed to make those projects succeed. Special Guest: Lak Lakshmanan. mlops, machine-learning, data-science, ai, artificial-intelligence, infrastructure, scale This week I spoke with Lak Lakhshmanan, who worked for years at Google on ML and AI projects and products at a senior level and he also brings years of experience working on meteorology and other scientific projects previously.

Lak brings a ton of experience to the table and it was interesting to hear his suggestions around when it is and isn't appropriate to bring the full set of MLOps tools to the table, for example. We also discussed the fundamentals of doing ML-backed projects as well as the teams needed to make those projects succeed.

Special Guest: Lak Lakshmanan.

Links:

]]> This week I spoke with Lak Lakhshmanan, who worked for years at Google on ML and AI projects and products at a senior level and he also brings years of experience working on meteorology and other scientific projects previously.

Lak brings a ton of experience to the table and it was interesting to hear his suggestions around when it is and isn't appropriate to bring the full set of MLOps tools to the table, for example. We also discussed the fundamentals of doing ML-backed projects as well as the teams needed to make those projects succeed.

Special Guest: Lak Lakshmanan.

Links:

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