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Deep Learning / Perception Technical Lead Manager (TLM), Self-Driving

Software, Advanced Technologies Group in San Francisco, CA

At Uber, we ignite opportunity by setting the world in motion. We take on big problems to help drivers, riders, delivery partners, and eaters get moving in more than 600 cities around the world.



We welcome people from all backgrounds who seek the opportunity to help build a future where everyone and everything can move independently. If you have the curiosity, passion, and collaborative spirit, work with us, and let’s move the world forward, together.


About the Role


Simply put, the Autonomy Capabilities team specializes in rapidly developing, prototyping, and landing large new autonomy features that allow our self-driving vehicles to do things they couldn't do yesterday -- e.g., autonomously navigating construction zones. Our team is unique in that we hire specialists across motion planning, perception, prediction, and control to work together to tackle these problems holistically, even when that means making sweeping architectural changes. With this role, we are looking for someone with strong technical vision, who can lead the development of new perception capabilities as we develop the next generation of architectures and algorithms for self driving. Are you interested?

What You’ll Do:
    • Lead the design of the state-of-the-art perception architectures and algorithms.
    • Define a vision and roadmap for the next-generation of perception architecture to support our team in landing new autonomy capabilities on the way to driver-less operations.
    • Collaborate effectively and build relationships with partners in Pittsburgh, Toronto, Boulder, and San Francisco.
    • Hiring - grow your team!




What You'll Need:


    • Experience working with state-of-the-art deep learning algorithms and convolutional neural network (CNN) architectures.
    • Familiarity with deep learning architectures relevant to perception, e.g., object detection, semantic/instance segmentation, early fusion, scene/instance flow, deep tracking, etc.
    • Good programming and design skills (we use Python and C++).
    • Familiarity with modern DL libraries and frameworks (we use Tensorflow and Pytorch).
    • Demonstrated ability to lead technical teams.
    • (Bonus) Experience applying research techniques to large-scale engineering challenges.
    • (Bonus) Experience writing high-quality software in industry or on large collaborative projects.
    • (Bonus) 4+ years of experience working on perception, self-driving, robotics, or related fields.
    • (Bonus) Graduate program in a related area.



About the Team

At the Advanced Technologies Group (ATG), we are building technologies that will transform the way the world moves. Our teams in Pittsburgh, San Francisco, Boulder, and Toronto are dedicated to mapping, software and hardware development, vehicle safety, and operations for self-driving technology. Our teams are passionate about developing a self-driving system that will one day move people and things around more safely, efficiently, and cost effectively.


At Uber, we believe technology has the power to make transportation more efficient, accessible, and safer than ever before. Self-driving technology has the potential to make these benefits an everyday reality for our customers, but it’s not going to happen overnight. Building best-in-class self-driving technology will take time, and safety is our priority every step of the way. Operating inclusively and transparently, while displaying responsible behavior in a structured development are critical to safety. We at ATG seek candidates who will role model these values.

See our Candidate Privacy Statement

At Uber we don’t just accept difference—we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. Uber is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.