Machine Learning Engineered

Apr 20 2021 32 ep. 76 mins 61

Machine Learning Engineered Podcast artwork

This podcast helps Machine Learning Engineers become the best at what they do. Join host Charlie You every week as he talks to the brightest minds in data science, artificial intelligence, and software engineering to discover how they bring cutting edge research out of the lab and into products that people love. You'll learn the skills, tools, and best practices you can use to build better ML systems and accelerate your career in this flourishing new field.

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Diving Deep into Synthetic Data with Alex Watson of Gretel.ai

Apr 20 2021 79 mins

Alex discusses his background working at the NSA and then starting Harvest.ai, which was acquired by and integrated into AWS. He then goes into his latest venture, Gretel.ai, which provides tools for creating anonymized and synthetic datasets.

A Practical Approach to Learning Machine Learning with Radek Osmulski (Earth Species Project)

Mar 30 2021 98 mins

Radek details his journey switching careers into software engineering and then into machine learning. He talks about mistakes he made, how he would do it now, and gives a preview of his forthcoming book.

From Data Science Leader to ML Researcher with Rodrigo Rivera (Skoltech ADASE, Samsung NEXT)

Mar 23 2021 83 mins

Rodrigo details his journey from selling a company to leading data science teams at top companies to researching machine learning. He also touches on his research interests in time series data and topological data analysis.

The Future of ML and AI Infrastructure and Ethics with Dan Jeffries (Pachyderm, AI Infrastructure Alliance)

Mar 16 2021 96 mins

Dan discusses why he's so excited about the future of machine learning, where it is on the technology adoption curve, the rise of a "canonical stack" of AI infrastructure, and practically approaching the hard problems in AI ethics.

Developing Feast, the Leading Open Source Feature Store, with Willem Pienaar (Gojek, Tecton)

Mar 09 2021 71 mins

Willem discusses his experience building the ML platform at Gojek and what he's learned from developing and open-sourcing Feast. He also goes into his vision for it's future and how teams can best get started adopting it.

Bringing DevOps Best Practices into Machine Learning with Benedikt Koller from ZenML

Mar 02 2021 88 mins

Benedikt discusses common problems faced by teams putting machine learning into production, bringing over best practices from DevOps to solve them, and building ZenML, an open source MLOps framework.

Starting an Independent AI Research Lab with Josh Albrecht from Generally Intelligent

Feb 23 2021 84 mins

Josh talks about pivoting from an AI recruiting startup to Generally Intelligent, an independent AI research lab. He also touches on how he defines general intelligence, what his lab is working on now, and how he creates the optimal research environment.

Industrial Machine Learning and Building Tools for Data and Model Monitoring with Evidently AI Co-Founders Elena Samuylova and Emeli Dral

Feb 16 2021 81 mins

Elena and Emeli of Evidently AI discuss what they've learned applying ML across a wide variety of industries, including manufacturing and industrial process improvement, and then go into why they've started building tools for data and ML monitoring as well as how teams can do it better.

Managing Data Science Teams and Hiring Machine Learning Engineers with Harikrishna Narayanan (YC Stealth Startup)

Feb 09 2021 75 mins

Harikrishna discusses what it means to be an effective data science manager and how he thinks about hiring for machine learning roles

Lessons Learned From Hosting the ML Engineered Podcast (Charlie Interviewed on the ML Ops Community podcast)

Feb 02 2021 63 mins

I was recently interviewed by Demetrios and Vishnu from the ML Ops Community podcast. We discuss my experience working as an ML engineer and starting the podcast, lessons learned from talking to experts, and trends we've noticed in the industry.