Josh Tobin: Research at OpenAI, Full Stack Deep Learning, ML in Production - Machine Learning Engineered

Episode 8

Josh Tobin: Research at OpenAI, Full Stack Deep Learning, ML in Production

Josh Tobin holds a CS PhD from UC Berkeley, which he completed in four years while also working at OpenAI as a research scientist. His focus was on robotic perception and control, and contributed to the famous Rubik's cube robot hand video. He co-organizes the phenomenal Full Stack Deep Learning course and is now working on a new stealth startup.

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01:32 Follow Charlie on Twitter (

02:43 How Josh got started in CS and ML

11:05 Why Josh worked on ML for robotics

15:03 ML for Robotics research at OpenAI

28:20 Josh's research process

34:56 Why putting ML into production is so difficult

44:46 What Josh thinks the ML Ops landscape will look like

49:49 Common mistakes that production ML teams and companies make

53:11 How ML systems will be built in the future

59:37 The most valuable skills that ML engineers should develop

01:03:50 Rapid Fire Questions


Full Stack Deep Learning

Domain Randomization for Transferring Deep Neural Networks from Simulation to the Real World

Domain Randomization and Generative Models for Robotic Grasping

DeepMind Generative Query Network (GQN) paper

Geometry Aware Neural Rendering

Josh's PhD Thesis

OpenAI Rubik's Cube Robot Hand video

Weights and Biases interview with Josh

Building Data Intensive Applications

Creative Selection

About the Podcast

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Machine Learning Engineered
Helping you bring ML out of the lab and into products that people love.

About your host

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Charlie You

Charlie currently works as a Machine Learning Engineer at Workday. He graduated from RPI with a B.S. in Computer Science and taught himself ML through online courses and projects. In his free time, Charlie enjoys investing and trading, playing poker, and training Brazilian Jiu-Jitsu.