Layoffs in Autonomous Driving: What's The Bottom Line? -- Demand For Core Talents Is Still Strong

Produced by Sohu Car · Car Cafe

The author is Liu Tongnan

In early March, it was fire and ice for Waymo, the self-driving technology company owned by Google's parent company Alphabet. Waymo is ranked by Guidehouse as the leader of the global self-driving industry. Meanwhile, Waymo announced its second round of layoffs this year.

With the first round of layoffs in early January, Waymo has cut 209 jobs, or 8% of its workforce. Waymo said in its statement that it was eliminating some engineer positions to "focus on business success." Although the industry is optimistic, but the profitability of the tight Waymo, still need to use the fastest way to cut costs, full focus on commercialization.

At present, limited by laws and regulations, technology maturity, automatic driving technology loading speed and other factors, the commercialization process of high-level automatic driving is seriously slowed down, low level automatic driving to pull up the vehicle product premium ability is insufficient, resulting in the commercial closed-loop cycle of automatic driving technology solution providers full of uncertainty. Therefore, some enterprises with poor industrial chain deployment and collaboration ability gradually struggle, and layoffs occur frequently.

Autonomous driving, on the other hand, is an all-around competitive field, combining technology, cost, talent and other factors. Among them, technology and cost barriers form a huge threshold. Talent competition is the key link to the prosperity of enterprises. According to Sohu Automotive incomplete statistics, from 2022 to now, there have been nearly 30 cases of talent flow in the field of autonomous driving, including job-hopping/poaching/recruitment of key executives.

How is the self-driving job market these days? Through further investigation and interview by Sohu Automotive, it is found that the industry still has a large demand for core talents. Meanwhile, although layoffs continue in the field of automatic driving, it is not entirely attributable to the winter market, and the lack of organizational planning ability of startup companies, the adjustment of talent structure within the industry and other factors are closely related.

Talent demand: senior talents in core positions are in short supply. There is a bilateral effect between top enterprises and talents

Regarding the wave of layoffs, Nick, a talent search expert in the autonomous driving industry, revealed in an interview with Sohu Automotive that "core talents are basically not in the scope of layoffs". According to Nick, core perception algorithms, control algorithms, location algorithms, prediction algorithms, simulation software, etc., are all core. Non-core jobs, such as operations, interns, and new kids, will face layoffs.

"The industry is still hiring," adds Nick. "Algorithmic talent is in short supply." Combined with the data from the Grime research, automated driving software engineer and algorithm engineer are the most popular jobs in 2022, accounting for 37 percent of newly created jobs. At the same time, there is a gap between talent structure and enterprise demand structure, and core talent recruitment becomes a difficult problem. According to Liepin's data, among the top 10 demands for autonomous driving, algorithm engineers account for the highest proportion, reaching 3.1%, while their talent supply accounts for less than 1.3%, which does not enter the top 10 of this index.

In addition, although autonomous driving is a relatively front-end field, the industry prefers people with mature and stable working experience. According to the logic calculation of "supply and demand ratio = resume quantity/job vacancy quantity", the gripper found that the supply and demand ratio of 5 to 10 years of working years reached the maximum, and the talent competition pressure was higher than that of other years of working years. By subdivision, the more senior the popular jobs are, the more unbalanced the supply and demand. Among them, the supply and demand ratio of engineers with 5-10 years of experience in algorithm, hardware, software and embedded is much lower than that of other technical jobs.

At the same time, the talent market prefers technical talents on the mass production side. According to industry insiders, there is not much demand for high-end positions in the field of automatic driving, but more demand is a large number of engineers with mature engineering ability, as well as a small number of mature and excellent algorithm engineers of a certain module, which requires quite high experience and ability. When it comes to autonomous driving talents, Nick admitted that compared with autonomous driving technology companies, candidates still want to work for companies like Wei Xiaoli. "In the end, to do solutions, they have to serve the Oems".

"Candidates for autonomous driving positions also want stable and reliable platforms." When Nick persuaded the candidates, he hoped that they could do some good projects on a better platform and polish their technology, because for them, their technology level is higher and they will be more valuable in the future.

With the change of market demand, enterprises need to establish multiple growth points, and even constantly change the business model. During this period, grabbing core talents is one of the most efficient means to complement the shortcomings of technology and even management. The core talents tend to head enterprises, to head enterprises gathered, or will become the catalyst to accelerate the industry reshuffle.

Talent adjustment: Enterprises anticipate risks and reduce costs to survive the recovery of the capital market

For start-ups, with the expansion of enterprise scale, organizational management and team efficiency have gradually become important factors affecting their operating costs. Therefore, personnel adjustment is also common.

For example, in the expansion stage, the enterprise needs a large number of talents to expand its business, and with the change of technology and market, the enterprise will adjust and optimize the redundant personnel according to the current development needs. In November 2022, the co-founder of U.S. autonomous driving company Nuro sent an email to employees saying that the surge in hiring over the past two years was a mistake. As a result, Nuro laid off about 20%, or nearly 300 employees.

In addition, along with the optimal allocation of limited resources, there will be talent adjustment. At the beginning of this year, Baidu IDG started to lay off employees. Nick revealed that the major cuts were in the intelligent transportation department, which specializes in cooperation between vehicles and roads. "The intelligent transportation department has poor profitability and mainly deals with government departments, so many projects may be faced before, and it is impossible to pay money even if it is done". For example, the team that provides the autonomous driving service for Jidu is still hiring, and the mass production pressure is not small.

"IDG also hired senior executives from Egatone earlier this year." The Egatone mentioned by Nick also saw layoffs in 2022, when the automatic driving department was fired. Nick believes that Egatone still has many problems in its cabin. Compared with doing two things (intelligent driving and intelligent cockpit) at the same time, it is better to put down the intelligent driving first and put all resources into making the intelligent cabin. Give the capital market a good account.

In the case of layoffs, there are many enterprises with problems in the capital chain, but there are also some enterprises with sufficient funds, but anticipate the risks in advance, adjust flexibly to better survive, and wait for the capital market to recover before financing or listing. In Nick's opinion, the current status quo is that companies are downsizing more for structural adjustment, to allow themselves to live a more cautious, stronger life.

In addition to Waymo, there are Mobileye, Baidu and Cruise, which are the leaders of the global autonomous driving industry rated by Guidehouse. For these four companies, whether they take L2+ route or L4 route, they all have one thing in common, that is, they have initially gone through commercialization in their respective fields and have a self-hematopoitic business model.

Conversely, even successful public launches with $5 billion valuations, like Embark Trucks, fail because they can't get their business model right. Embark Trucks, which focuses on autonomous trunk logistics, has a clear path, but it has only delivered one vehicle in seven years and has been operating at a loss for a long time. This week, Embark Trucks announced that it will lay off 70% of its workforce. The remaining employees will be responsible for winding down the company's operations, making it the first publicly listed autonomous driving company to declare bankruptcy and shut down.

Embark Trucks CEO stated, "After a thorough review of all alternatives, we were unable to determine the path forward for the business in its current form; The capital markets have turned their backs on unprofitable companies."

Enterprises that rely only on external blood transfusion are difficult to survive, and enterprises that gradually acquire self-hematopoietic ability can truly enter the growth stage. Those enterprises whose technological mass production capacity has been tested by the market, who do a good job in capital risk control and flexibly adjust their business models when capital shrinks, can still find their own position, and gradually move to the forefront with the goal of landing in the industry crisis.