Aurora delivers the benefits of self-driving technology safely, quickly, and broadly.
Pittsburgh, PA, US
San Francisco, CA, US
Bringing self-driving vehicles to our roads is the most transformative opportunity of our generation. Aurora is taking a fresh start with the development of self-driving technology, combining excellence in AI, rigorous engineering, and a team with decades of experience building robots that work.
Led by a team of seasoned experts, our mission is to deliver the benefits of self-driving technology safely, quickly, and broadly. We are designing the software and hardware to power the transportation of our future that will make our roads safer, give more people access to mobility, and reduce congestion and pollution in cities - improving the quality of life for all. The challenge in what we are endeavoring to achieve is transcendent; we are developing perhaps the world's most complex computing system and asking it to perform the task of transporting and keeping safe our most precious asset: human life.
Aurora hires people who are excited to build the future of transportation. This candidate will partner closely with autonomy and ML platform engineers, product managers, and designers to streamline and scale the end-to-end machine learning data and model pipeline. You’ll gain a deep understanding and advocate for the users who are building and managing machine learning model development. You define tools, services, and workflows that enable faster development cycles, scale to many parallel experiments, and maintain precise tracking and traceability of every version. Your work is critical to accelerate the core mission of the company to bring the Aurora Driver to market safely, quickly, and broadly.
- Define the vision for a multi-year product roadmap for your product area, collaborating with PM, Design, Engineering, and other stakeholders to build a highly reliable machine learning platform that accelerates our autonomy development lifecycle.
- Engage with key stakeholders to facilitate tradeoff decisions and prioritize key deliverables that align to company milestones.
- Effectively communicate product strategy and roadmap, from executives to individual team members, bringing clarity to the ‘what and the why.’
- Conduct market and user research to deeply understand the state of the art in your space and how that maps to your team’s use cases. Propose open-source and commercial solutions where applicable, and set direction for the technologies that can be developed internally.
- Manage product risks and ensure valuable outcomes are delivered to the organization.
- Author Product Requirements Documents that contain clear and deep thinking about the purpose of proposed solutions, the outcomes they will drive, key success metrics, and the features needed to realize the potential.
- 2+ years of product or program management experience or 5+ years of relevant experience
- Engineering, Business or equivalent degree, with strong technical aptitude and skills highly preferred
- Experience in leading product development of complex systems on modern technology platforms
- Experience in machine learning model development and related platforms.
- Experience with data intensive platforms and systems that depend on large scale infrastructure. AWS services expertise is a plus.
- Experience building complex, distributed systems to enable enterprise workflows.
- Proficiency in metrics development and analysis, data visualization, and basic scripting languages.
Working at Aurora
Our work has real purpose. Delivering the benefits of self-driving will save lives around the world, expand access to transportation, revitalize cities, and give people time back every day.
We’re one team. We’re inspired by the challenge of what we’re solving and the impact our work will have on society. Our camaraderie is built on respect for our work and the fundamental belief our success will be a result of working together.
The Founding Team
Aurora has assembled the most experienced leadership team in the space. Chris Urmson helped lead Carnegie Mellon’s efforts in Darpa’s Grand Challenges, then was a founding member of Google’s self-driving team. Sterling Anderson worked on the tech at MIT before leading Tesla’s Autopilot system. Drew Bagnell, also a Carnegie Mellon alum, is a machine learning expert who helped build Uber’s autonomy effort. At Aurora, these three continue to bring experts from all areas of the industry to the team. We are funded by Amazon, T Rowe Price, and some of Silicon Valley’s best venture capital firms, including Sequoia, Greylock and Index Ventures.