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Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
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Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Technology & Innovation [HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
[HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy
Autonomous driving has reached the point where the question is no longer whether the technology can work. The harder question is whether it can work safely, reliably, and affordably—in real cities, with real passengers, on real ride-hailing networks.
That is the frontier Laura Major is working to cross.
As President and CEO of Motional, Major is leading one of the most difficult transitions in mobility: moving Level 4 autonomous vehicles from development programs into commercial operation. Her career has been built around human-autonomy interaction and advanced autonomous systems across space, air, ground, and sea. At Motional, that experience now converges on one mission: turning autonomous-driving technology into a system passengers, cities, communities, and ride-hailing partners can trust.
From her perspective, autonomy is not finished when it works in controlled environments. It is finished when it performs safely and predictably on public roads.
Laura Major’s career has been defined by one central question: how humans and autonomous systems learn to work together.
That focus began at Georgia Tech and MIT, where she earned a Master of Science degree, and continued at Draper Laboratory, where she led teams developing advanced autonomous solutions across space, air, ground, and sea.
The work was never confined to one type of machine. Major helped develop new capabilities for special operators conducting advanced battlefield missions. She later became CTO of Aria Insights, where she worked on unmanned aerial vehicles for indoor inspection. Her path then led to Aptiv, where she took on the CTO role and helped form the joint venture that established Motional.
At Motional, she continued as CTO, leading the delivery of the company’s first-generation autonomous-driving system. After five years in that role—and after delivering Motional’s second-generation autonomous system and integrating it with Hyundai Motor Group for the IONIQ 5 robotaxi, including pilot deployments with Uber, Uber Eats, and Lyft—Major was appointed President and CEO of Motional in 2025.
The throughline is clear: human-autonomy interaction, mission-critical systems, and the practical challenge of moving advanced technology into real operations.
“I’ve had a strong focus on the interaction of people and autonomous technology throughout my career,” Major says.
That experience now shapes the way she leads Motional. The goal is not simply to develop autonomous-driving technology. It is to build a system that can become part of the transportation fabric. For Major, the work sits at the point where autonomy becomes infrastructure.
One of the most important decisions Major has made at Motional was also one of the hardest: shifting the company’s autonomous-driving system to an AI-first architecture.
Motional had momentum. Its technology was advancing. Its commercial operations were moving forward. But Major and her team saw an opportunity to rebuild the system around the latest advances in artificial intelligence, which was required to put Motional in a stronger position for scalable, cost-effective autonomy.
A major accomplishment I’m particularly proud of was the transition of our autonomous-driving system to be AI-first, we saw the opportunity to completely rearchitect our system to incorporate the cutting edge in artificial intelligence.
President and CEO of Motional
That decision required a pause. It meant slowing progress in some areas so the company could make a deeper architectural change. The result, Major says, is an autonomous-driving system built to enable Large Driving Models, or LDMs.
The ambition is not only stronger performance. It is a different path to scale.
With LDMs, Motional is working toward more human-like driving behavior, faster improvement through end-to-end learning, and more generalizable reasoning that can accelerate deployment in new cities. At the same time, the system is being built with the visibility and safeguards required to meet rigorous safety expectations.
For Major, the AI-first shift is not about replacing safety discipline with a black-box model. It is about combining modern AI with the structure required for responsible deployment.
The choice was to give up some short-term momentum in order to build a stronger long-term foundation.
For Motional, the IONIQ 5 robotaxi is one of the clearest demonstrations of what its partnership with Hyundai Motor Group can deliver.
It was not a conventional vehicle retrofitted with autonomous technology after the fact. It was designed from the beginning as an autonomous vehicle for ride-hailing.
The delivery of the IONIQ 5 robotaxi in partnership with HMG was one of, if not the first, autonomous vehicles custom designed for ride hailing.
President and CEO of Motional
That distinction matters. In autonomous vehicles, the car and the autonomous-driving system cannot be treated as separate pieces. The compute platform, sensor suite, validation process, and manufacturing plan all have to work as one.
Developed with Hyundai Motor Group, the IONIQ 5 robotaxi was engineered, tested, and manufactured as an integrated autonomous platform. It came off the assembly line at the Hyundai Motor Group Innovation Center Singapore.
For Major, this is where partnership becomes product.
The project brought together Motional’s autonomy expertise and Hyundai Motor Group’s vehicle engineering, manufacturing capability, and production discipline. It also showed how a robotaxi can be built around the operational demands of ride-hailing from the start.
“I consider the IONIQ 5 robotaxi the first major demonstration of the powerful potential of what HMG and Motional can do together and it is only the beginning,” Major says.
That potential is not only technical. It is operational: the ability to build autonomous vehicles with the integration, validation, and manufacturability required for commercial fleets and also the opportunity to bring the power of autonomy to personal vehicles.
In that sense, the IONIQ 5 robotaxi is more than a pilot vehicle. It is proof that the system around the robotaxi matters as much as the autonomy inside it.
Motional is taking a different path from many companies in the autonomous-vehicle industry.
Some players are relying on specialized machine-learning models. Others are moving toward fully end-to-end autonomy. Motional’s approach sits between those poles: state-of-the-art AI, reinforced by proven safety backstops, and aimed at responsible, affordable autonomous vehicles.
Motional is taking a different path than others in the industry, we are combining the best of state-of-the-art AI innovations with tried-and-true safety backstops.
President and CEO of Motional
At the center of that approach are Large Driving Models. Motional is developing LDMs to bring embodied foundation models into its autonomous-vehicle stack, with the goal of translating AI breakthroughs into systems that can expand to new cities with less dedicated development.
This is where Motional sees its technical edge.
By optimizing the number of machine-learning models in the AV stack and giving them the right learning capacity, Motional aims to preserve introspection—the ability to understand what is happening inside the system and improve it with discipline. That matters especially for long-tail issues: the rare, difficult edge cases that define the hardest parts of autonomous driving.
The goal is a system that can reach driverless safety benchmarks while reducing the cost and effort required to expand across regions.
For new joiners, that creates a demanding technical environment. Engineers at Motional are not being asked to maintain a legacy stack at the margins. They are working as the company moves past heuristic systems toward a unified, AI-first autonomy architecture.
That work includes next-generation AI, Large Driving Models, embodied foundation models for end-to-end machine-learning motion planning, transformer-based scene encoding, and reinforcement-learning architectures capable of turning massive multimodal sensor streams into safe, real-time driving decisions.
The same shift is happening in the data layer. Motional’s Continuous Learning Framework is being built to ingest petabytes of daily fleet data, mine rare edge cases, trigger automated labeling pipelines, and retrain machine-learning models concurrently.
The goal is a fleet that gets smarter with every mile driven.
The work also extends into 4D data visualization and visual web applications. Front-end and full-stack engineers are not simply building dashboards. They are solving four-dimensional data problems, creating custom web interfaces that use WebGL and WebGPU to render and manipulate gigabytes of 3D point clouds and temporal sensor data directly in the browser.
Predictive motion forecasting is another core challenge. Anticipating what human drivers and pedestrians will do next remains one of robotics’ hardest problems. Motional researchers have worked on consistency-based machine-learning methods, including cycle-loss architectures, to ensure that an agent’s predicted future trajectory aligns logically with its past observations.
That work is aimed at reducing uncertainty in dense urban environments.
The technical scope also reaches the vehicle itself. Hardware engineers work with manufacturing partners to integrate redundant lidar, radar, and camera systems into the IONIQ 5 robotaxi platform. Human-machine interface teams, meanwhile, build accessible in-cabin experiences designed to bridge the gap between complex robotics and passenger trust.
At Motional, you aren’t a hid-den cog in a legacy corporate machine, every line of code you write or model you train directly impacts a commercialized, autonomous fleet operating on public roads.
President and CEO of Motional
That is why Major sees this moment as especially important.
Motional is entering what she calls the most important and rewarding phase of technology development: commercialization. For the company, that means operating driverless robotaxis on the Uber network in Las Vegas by the end of this year.
This is the ultimate test of the engineering, development, and validation work the team has done. But Major sees it as only the beginning.
As Motional continues training its Large Driving Models, the system is expected to become more capable and support faster expansion to new cities. At the same time, the company will gather feedback from ride-hailing partners and riders to improve the product, from pre-positioning strategy for better estimated arrival times to more human-like driving behavior and better in-cabin experiences.
This is where AI, fleet learning, passenger experience, and commercial operation begin to reinforce one another.
For Motional, the next phase is not just about proving that the robotaxi can drive. It is about proving that the entire system can learn, improve, and scale.
As Motional scales its commercial operations, Major is looking for engineers and operators ready to move beyond research and development into the rigor of real deployment.
The talent profile is demanding. Motional needs world-class technical fundamentals, but also the operational grit required to ship Level 4 autonomous systems at scale.
Production focus is central. Code is not finished when it works in a simulator. It is finished when it performs deterministically on an embed-ded system in the wild.
That requires deep knowledge of modern AI, strong software fundamentals, high-throughput cloud infrastructure, and hardware-software co-design. It also requires an instinct for constraints: latency, memory, compute efficiency, and the realities of automotive-grade systems.
A systems mindset is just as important. Whether the work touches visualization, data pipelines, vehicle hardware, or in-cabin experience, every component affects the safety and behavior of the full autonomous-vehicle ecosystem.
Level 4 autonomy also demands first-principles thinking. Edge cases appear every day, often without obvious solutions. Engineers need to break unfamiliar problems down logically and solve them from the ground up.
Cross-functional collaboration is part of the job. A single autonomous ride depends on perception, planning, cloud routing, ruggedized hardware, and passenger experience. Engineers must be able to translate complex technical dependencies across very different disciplines.
“We are building a culture of high ownership, rigorous safety, and intellectual honesty,” Major says.
For candidates, Motional offers a rare combination: the backing and manufacturing power of Hyundai Motor Group, with the speed, ownership, and equity upside of a focused technology company.
As Motional launches driverless commercial operations and expands into new geographies, its engineering scope is growing rapidly. That creates an environment built for acceleration.
The career path is not built around silos. Engineers are not confined to optimizing one small feature for years. Because of Motional’s focused scale, they can work across the stack and understand how complex multimodal AI models connect with automotive hardware.
Growth is driven by impact, not tenure. As commercial fleets expand, Motional is solving high-dimensional engineering problems that have not been solved before. That creates immediate opportunities to own critical architecture and lead technical initiatives.
Major sees the work as career-defining.
Shipping a product is difficult. Commercializing a Level 4 robotaxi fleet on public roads is something else entirely. It requires systems thinking, safety rigor, and machine-learning expertise at the edge of the global engineering landscape.
Motional’s promise is the ability to take calculated technical risks with stability behind them—and without being slowed by unnecessary corporate red tape.
“If you want to look back at your career and point to a driverless fleet changing the fabric of urban transit and say, ‘I contributed to the architecture that made that happen,’ Motional is where you build it,” Major says.
For engineers interested in AI-first autonomy, large-scale fleet learning, and the real-world deployment of Level 4 systems, the HMG Tech Talent Forum offers a direct view into the people and technology shaping that future.
Kyeongjin Kim
kyeongjin.kim@hyundai.com
Global PR Team 1 · Huyndai Motor Company
Disclaimer: Hyundai Motor Group believes the information contained herein to be accurate at the time of release. However, the company may upload new or updated information if required and assumes that it is not liable for the accuracy of any information interpreted and used by the reader.
About Hyundai Motor Group
Hyundai Motor Group is a global enterprise that has created a value chain based on mobility, steel, and construction, as well as logistics, finance, IT, and service. With about 250,000 employees worldwide, the Group’s mobility brands include Hyundai, Kia, and Genesis. Armed with creative thinking, cooperative communication and the will to take on any challenges, we strive to create a better future for all.
More information about Hyundai Motor Group can be found at: http://www.hyundaimotorgroup.com or Newsroom: Media Hub by Hyundai, Kia Global Newsroom, Genesis Newsroom
![[HMG Tech Talent Forum 2026 Series ④] Laura Major, President and CEO of Motional; The Road to Commercializing Level 4 Autonomy Autonomous driving is entering a new phase. The race is no longer about proving that robotaxis can drive—it is about proving they can operate safely, reliably, and profitably at commercial scale. In this interview, Motional CEO Laura Major explains why the company's AI-first strategy, Large Driving Models, and partnership with Hyundai Motor Group are designed to close that gap, and what it will take for engineers to help bring Level 4 autonomy into everyday transportation.](/content/dam/hyundai/ww/en/images/newsroom/news-image/news-release-basic.jpg)
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