Research and Production

I just had lunch yesterday with a young engineer who works for a big SaaS software firm and would love to get a job working on autonomous vehicles. But, he asked, how hard is that to pull off without going to grad school?

Later yesterday I responded to some inquiries from potential Udacity students about jobs in the self-driving car industry. Same question: do I need a PhD to land a job in the industry?

At Udacity we are building a Self-Driving Car Nanodegree and we’re doing it because there’s a huge interest in this area and companies need to hire a lot of engineers! We wouldn’t be doing it if we thought you had to get a PhD to work on self-driving cars.

A lot of that demand for engineers, it turns out, comes from the transition of autonomous vehicles from research to production.

Until recently, autonomous vehicles were largely under the umbrella of the research divisions of large companies. Those research divisions are much smaller than production divisions, and they’re staffed by folks with sterling academic credentials — PhDs in computer vision and deep learning and robotics. They’re great at pushing the cutting edge.

What research divisions are less great at is pushing out products, because they’re not designed for that.

Production divisions tend to be staffed by terrific engineers who are focused on shipping code. These engineers are often not PhDs or cutting-edge researchers. They’re more oriented towards getting a product built, testing it, and scaling it.

There also tend to be a lot more engineers, just in absolute numbers, in production areas than in research.

The migration of autonomous vehicles from research to production is a big reason why this is a terrific time for engineers to move into the field of autonomous vehicles.

As my friend Jinesh from Ford said:

“It’s helpful to know C++ or to have experience with human-machine interaction. But being adaptable and a quick learner is more important since companies that design and build robotic cars may be using a different mix of technologies or applying them in different ways.”

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