Choosing a Career Path in Machine Learning to Maximize Impact
When you work in area that is in demand, like Machine Learning is right now, there are many options available. Since we closed Idibon, the company I was running until recently, I have been weighing up my next step.
Those of you who know me, know that I always look for the way to have the biggest impact in the world. We founded Idibon with the goal of bringing language technology to all the world’s languages. Prior to that, I completed a Stanford PhD focused on how Machine Learning can be used for disaster response and health in low resource languages; used machine learning and crowdsourcing to track epidemics; worked for the UN supporting refugees in West Africa; and worked in documenting the world’s endangered languages.
My most recent job decision spanned the full range of companies, from founding a new company, to joining the executive team of an existing startup, or leading machine learning initiatives at some of the world’s largest companies. Every one of the opportunities was at an organization with people I greatly admire. Every role would have seemed like an unrealistic dream-job just 5 years ago, before Machine Learning was recognized as a key component of technology.
Cutting edge computing: the Antikythera mechanism! Note: picture is slighted dated due to several advances in technology since 150-100 BCE (source: Wikipedia)
I ultimately decided to join Amazon Web Services, as a Principal Product Manager for Machine Learning. Like the over 1 million companies using AWS, I built my last three companies using the AWS Cloud. I’ll now be helping companies take advantage of sophisticated Deep Learning and Machine Learning technologies that most could never have built within their own engineering teams.
Stay tuned for official announcements about exactly what we’ll be building!
Robert Munro
October, 2016
