How the ML Product Got Built with Jesus Martinez

Jesus Martinez, Senior Engineering Manager of  Machine Learning at Planet, walks us through how the ML product was built at Planet. He also talks about balancing R&D and Delivery Teams in the ML space.

• Challenges in building machine learning products.
• R&D techniques, processes, and challenges.
• Skill set needed from a software engineer.
• New Territories. New People (the hiring process)
• The vision of  “Help Life on Earth Using Space”
• R&D spending and monetization
• Balancing Research Development and Delivery
• Importance of communication within the company.

About today’s guest:

Jesus is originally from Sevilla, Spain. He studied physics and then moved to the US to become an astronomer. His research focused on analyzing infrared images from deep space to measure the clustering pattern of galaxies and infer how much dark matter exists around them. After his Ph.D., he moved to San Francisco and transitioned to a career in data science. Today, he leads the applied ML team at Planet, which is a leading company in the Earth-observation space. His team builds core machine vision feeds that transform global streams of images into maps, alerts, and insights.

LinkedIn: https://www.linkedin.com/in/jmartinezmanso/

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