Transform 2021

Elevate your enterprise data technology and strategy.

July 12-16

After what feels like a lifetime of lockdowns, restrictions, and hitting pause on life, things are slowly returning to normal. And frankly, we couldn’t be happier. During this global pandemic, countless businesses all over the world introduced hiring freezes, furlough schemes and had to make some tough decisions. But there has been a shift, and we have front row seats. The world is returning to work, and this has resulted in some pretty amazing companies setting off on hiring sprees, with growth ambitions for the next few months.

And that’s what brings us here today. We wanted to shine a bit of a spotlight on three brilliant jobs that are open right now, and give you a bit of cool information about them.

Senior Staff Engineer, Backend — Hosting, Airbnb

Core Hosts are the heart and soul of Airbnb and their truest differentiator. Hosts are the brand and enable amazing travel experiences for guests. They are ordinary people who had the courage to share their primary and secondary homes with complete strangers across the world.

As a senior technical individual contributor, you will partner closely with the CTO of Hosting and senior leaders across the broader technical organization. Although you will be at one of the highest levels of seniority, all individual contributors at Airbnb are Software Engineers which means we expect you to be hands on and contribute code.

The successful candidate will define overall technical architecture for major parts of the Hosting business, and architect large-scale reliable systems to support continuous growth of the business. They will also influence the organization, engineering leaders, product managers, and the business to develop a unified approach to overall Hosting architecture.

Linux/DevOps Engineer, Apex Tech Solution

Apex Tech Solution is looking for a System Administrator to maintain, upgrade, and manage their software, hardware, and networks. Resourcefulness is a necessary skill in this role. You should be able to diagnose and resolve problems quickly. You should have the patience to communicate with a variety of interdisciplinary teams and users. Your goal will be to ensure that their technology infrastructure runs smoothly and efficiently.

The successful candidate will be responsible for installing and configuring software and hardware, managing network servers, and technology tools. They will monitor performance and maintain systems according to requirements, and also take the lead on troubleshooting issues and outages. In order to be successful in this role, you will need to have proven experience as a System Administrator, Network Administrator, or similar role, along with extensive experience with databases, networks (LAN, WAN), and patch management. Knowledge of system security (e.g. intrusion detection systems) and data backup/recovery is also a plus.

Senior Staff Software Engineer, Foundational Modeling, Airbnb

Everyone at Airbnb thinks about trust, but this team obsesses over it daily. At the core of trust is safety, and they spend a significant amount of their time and energy keeping the community safe. The Trust Org is responsible for protecting the Airbnb community and platform from fraud while also ensuring that hosts, guests, homes, and experiences meet high standards. They constantly work to fight against online and offline fraud. They also work on the onboarding and screening of users, and think about complex topics such as identity to ensure that every interaction with Airbnb helps build trust. Trust Engineering within the Trust Org is responsible for the technology vision and development of a complex stack that runs on every key interaction on the platform.

They’re looking for a senior staff engineer to join their Foundational Modeling team (part of Trust Engineering) that is responsible for a Machine Learning Platform, a core capability that enables Trust product teams to build machine learning solutions to stop bad actors from doing bad things on Airbnb. As a senior staff engineer on the Foundational Modeling team, you will help keep Airbnb users safe by working across diverse teams and systems to enable sophisticated safety strategies. You are eager to understand complex systems top to bottom and thrive working across technologies and codebases.

Transform 2021

Elevate your enterprise data technology and strategy.

July 12-16

Presented by Pony.ai

The vision of safe, reliable autonomous vehicle transportation at scale is closer than ever to being realized, says James Peng, CEO at Pony.ai. Since the company’s founding in Fremont, California in late 2016, the company’s been making strides in autonomous mobility deployment in both the U.S. and China. The company was the first to launch and offer a public-facing Robotaxi service in both countries.

“The technology is moving from experience-level to application,” Peng says. “The first half of the game is to build stable and mature products and accumulate experience. The second half is to move from R&D to mass production and scale, in addition to achieving commercially viable products.”

In 2019, Peng predicted that the world would see a wide adoption of fully autonomous driving vehicles on the open roads within five years, and that forecast is gaining momentum. Pony.ai just received a driverless permit from California DMV, a milestone for their engineers to perform driverless testing without a human driver behind the wheel on public roads within the state. These tests are accelerating commercial growth across their operation sites worldwide, and they plan to launch driverless Robotaxi service to the public in California starting in 2022.

“I’m pretty confident that in many of the larger cities in the U.S., people will soon be able to ride with a driverless Robotaxi vehicle,” says Tiancheng Lou, CTO at Pony.ai. “A significant portion of taxi services will be supported by driverless vehicles.”

Pony.ai currently offers ride-hailing in its autonomous vehicles in five markets: Irvine and Fremont in California; as well as Beijing, Shanghai, and Guangzhou in China. The company plans to install its technology in hundreds of vehicles next year, rising to tens of thousands in 2024-2025.

Waymo, Google’s self-driving car arm, has been piloting a fleet of fully driverless robotaxis in Phoenix for the past year, while Amazon-owned Zoox unveiled its autonomous robotaxi service last December.

The goals of autonomous driving

According to most companies, the biggest benefit of autonomous driving is safety. The U.S. Department of Transportation has reported that 94% of car crashes are caused by human error. While overall driving was down in 2020 because of the pandemic, traffic fatality rates surged 24% — the highest spike in nearly a century. Autonomous driving is the solution to this issue, Peng says, and companies like Pony.ai, Google, and Uber, along with most of the major automakers, are sinking considerable money into R&D, optimistic about the future of autonomous driving.

A transition to autonomous vehicles also has potential to reduce greenhouse gas emissions and support U.S. economic growth, points out the Self-Driving Coalition for Safer Streets. The coalition, which includes members Ford, Volvo, Lyft, Uber, and Waymo, promotes the benefits of fully self-driving vehicles and supports the fastest deployment possible – or advancing the scale of the technology, which would enable mass production and start moving autonomous vehicles to the center of the smart city vision.

Challenges of driving autonomy at scale

Pony is hoping to achieve large enough scale to reduce costs and meet commercial needs by 2022 with Alpha X, the working name for their latest generation of autonomous vehicles, Lou says, which are designed to be manufactured on a production line.

“To have a large number of vehicles, we need to manufacture them in a standardized way,” Lou says. “It’s a critical step to achieve front-loading mass production of self-driving cars.”

The company established a production line and a set of standardized processes specifically for L4-level autonomous driving systems last November. With the support of the production line, the production efficiency of the autonomous driving system doubled six times compared with the previous generation, and production pace accelerated.

With PonyAlpha X, they established a L4 level autonomous driving system scale production line, Lou says. To manufacture the vehicle, they established a supply chain management process, hardware module design and verification, test production, and car conversion before final assembly. The end phase consists of overall quality inspection, off-line calibration, and road testing. The project helps them set up a standardized production process, which shortened production time, effectively reduced costs, and improved the stability of the overall system.

Compared with the previous generation, PonyAlpha X is more compact, integrated, and lightweight in terms of system hardware integration, reducing the cost of post-maintenance. They recently partnered with Toyota to equip PonyAlpha X on Lexus RX models.

In February of this year, the company rolled out the new self-driving vehicles equipped with the latest generation system from the standardized production line. The cars will go through all-day autonomous-driving open-road tests in Guangzhou, Beijing, and Shanghai before they join the company’s Robotaxi fleet for large-scale operations.

Their recent partnership with Luminar, an autonomous vehicle sensor and software company, has also allowed them to significantly bring down the cost of manufacturing, which is always a major hurdle for mass production.

“For the next generation, one of the biggest challenges is we’re trying to use auto-grade sensors,” Lou says. “One of the critical pieces is Luminar LiDAR. Using that LiDAR, we’re moving one step toward to being ready for mass production, and then we can prepare for large scale production. Luminar LiDAR, compared to our current solution, is more reliable and much cheaper.”

LiDAR is a laser sensor that sends millions of laser points out per second and measures how long they take to bounce back, a key component to safe autonomous driving. Luminar says that its Iris LiDAR has a maximum range of 500 meters (1,640 feet), including 250-meter range with less than 10 percent reflectivity. The self-driving sensor solution offers better perception accuracy and field of view breadth to enhance the ability to cope with long-tail scenarios. The new pony vehicles with Luminar’s LiDAR sensor will be up and running in 2022, and will be ready for the company’s robotaxi customers in 2023.

Autonomous driving at scale is, literally, in sight

The past year hasn’t been easy, Lou says, but it pushed their contactless delivery initiative further along in Irvine, which helped the community cope during the pandemic, while adding testing and collecting mileage for data points. But full autonomy at scale still requires testing.

To help accelerate their commercial growth and global deployment, they’ve tapped Lawrence Steyn, vice chairman of investment banking at JPMorgan Chase & Co, as chief financial officer.

And looking ahead, in 10 years or 20 years, it could be possible that owning a vehicle would entirely be a luxury, Lou says.

“We need to carefully think about whether that’s necessary, having personal vehicles,” he says. “If it’s mathematically possible to get a vehicle within as little as 30 seconds, most people may not have to own a vehicle.”

He also points out that if most vehicles are running autonomously, the vehicle form factor can be reshaped for accessibility, opening up safe transportation for a larger population of older and disabled riders who could turn to cheaper, more efficient autonomous transportation for their travel needs.

“I still keep the engineering part in me, and with that part, I dream of pushing the world forward with state-of-art technology,” Peng says. “We are working hard to largely scale and deploy our technology across countries and regions to benefit more and more people.”

Dig deeper. Learn how Pony.ai is building the future of autonomous driving at scale.

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