Engineering jobs in the Autonomous car race in Silicon Valley

From GM’s $581m purchase of Cruise, Uber’s $680m Otto acquisition and Ford’s $1bn Argo Ai project, the rush to develop self-driving cars is fueling lucrative deals for autonomous tech firms, and has made the founders of those startups wealthy. But in the epicenter of this particular race there’s a tight supply of seasoned computer scientists and engineers needed to perfect the technology, giving rise to considerable salaries for top talent.

Salaries in the Bay Area, including annual bonuses and equity, currently average $295,000 a year for top self-driving car engineers, and range from $232,000 to as much as $405,000, based on data from Paysa, a Palo Alto firm that analyzes pay and job trends using an artificial intelligence-enabled data platform. The average is more than four times the California median household income of $64,500 in 2015 and over five times the U.S. average, based on Census figures.

Salaries are so high because the pool of talented engineers is somewhat limited right now, Paysa CEO Chris Bolte told Forbes.

“We see this type of engineer as one of the hottest engineers out there.” Self-driving cars, along with virtual reality and augmented reality, machine learning and AI are all on a “wild upswing,” he said.

“These far-reaching categories that are shaping the future of things, that’s where companies are putting major investments,” Bolte said. “The competition for these people, it’s pretty outstanding, which is why you see such big salaries.”

The race to master and commercialize robotic vehicles that can serve as taxis, delivery vans or heavy trucks, has grown intense with the automotive and tech worlds, given how large a shift it may mean for society. Advocates see the likelihood of dramatic reductions in traffic accidents and fatalities; reduced congestion and stress-free commutes with passengers free to text, read, email, watch videos or sleep while in transit.

“It’s not just the physical car but areas like navigation, LiDAR, cameras, etc. are all growing so the need for talent, both in hardware and software, is huge,” Sebastian Thrun told Forbes.

He should know. He’s a research professor at Stanford University and founder of Udacity, an online educational service that’s the first to offer a “nanodegree” designed to train engineers for autonomous vehicles.

In the world of autonomous vehicles Thrun is a superstar. He was the first leader of Google’s Self-Driving Car project, a job he took after managing Stanford’s winning teams of computer scientists, engineers and roboticists in the Defense Department’s DARPA competitions, the legendary 2005 Grand Challenge and 2007 Urban Challenge. (Those events handed out just a few million dollars in prize money, but were the virtual Big Bang of self-driving car tech.)

Since kicking off the Self-Driving Car Nanodegree program in September, Udacity has received applications for it from 25,000 people and currently has more than 5,000 students enrolled in course, spokeswoman Amy Lester told Forbes.

“There is some very good talent out there but right now it’s more of a talent grab at companies,” Thrun said. “We are attempting to fill this talent gap and have people (get) the right skills.”

Two big players in autonomy exemplify that demand and are at the high end of the handsome pay trend.

Google (which now operates its program as Waymo) offers $283,000, including pay and equity, and excluding a $30,000 signing bonus, Paysa data show. Total compensation from Uber for self-driving car engineers is even higher at $348,000.

Coincidentally, the companies are also locked in a bitter lawsuit. Waymo claims Anthony Levandowski, formerly one of Google’s high-level engineers, stole trade secrets related to is laser LiDAR sensor technology, a crucial part of the vision system that lets driverless cars see their surroundings in 3D and 360°. The LiDAR mapping display in Uber’s self-driving Ford Fusion (Uber).

Uber made the biggest splash with its program, inaugurating a so-called self-driving vehicle service in Pittsburgh last September (despite the fact that each car had two human technicians in the front), a month after it acquired Levandowski’s driverless truck tech startup Otto. Efforts by Uber to replicate the Pittsburgh program in San Francisco late last year fell apart after a standoff with California’s Department of Motor Vehicles when Levandowski refused to apply for a permit to operate its automated test vehicles.

Compounding those headaches, an Uber self-driving Volvo being tested in Tempe, Arizona, was struck and badly damaged in a collision on March 24^th. No serious injuries were reported but the company subsequently suspended road tests of its autonomous vehicles, at least for now.

That’s a setback as Uber CEO Travis Kalanick has tied the ride-hailing giant’s future to mastering driverless technology.

“We are incredibly excited by the potential for self-driving cars to further our mission of bringing reliable transportation to everyone, everywhere,” he said in a recent blog post. “They will also help to reduce traffic accidents, which today kill many people a year; free up the huge amount of space currently used to park the world’s billion-plus cars; and cut congestion, which is choking our cities.”

Challenges to Uber’s young program aren’t likely to prevent it or competitors from their hunt for talent. Paysa data show there are currently more than 200 positions available for self-driving car engineers from a host of companies including Apple, Ford, Tesla, Bosch, Here, Valeo, Delphi, Lucid, GM, nuTonomy and Drive.ai.

“We are at the start of an entirely new period in human history with autonomous vehicles,” Thrun said. “I expect (the competition for talent) to continue for some time.”