Waymo
autonomous driving technology
SoftwareEngineer,PinInfra
Neural analysis suggests this role is
optimal for Mid candidates.
“Software Engineer, Pin Infra at Waymo. Skills: infrastructure, scalable solutions, demand control, congestion management, ML integration. Collaborate with Machine Learning (ML) teams to integrate new location selection models to improve pin quality. Centralize critical location logic to ensure consistency and improve service reasoning”
What You'll Achieve.
improve pin quality; ensure consistency; improve service reasoning; manage congestion; precisely manage Pick-up and Drop-off (PUDO) behavior; debug and proactively identify customer pain points; performance tuning; reducing latency; scaling critical backend systems; improve system architecture; improve maintainability; improve diagnostic capabilities
Industry & Context.
solve complex technical challenges
What They're Looking For.
Must Have
Experience building and scaling high-performance infrastructure for critical services, 3+ years of experience, C++ (or another OOP language) proficiency
Nice to Have
Prior experience working with autonomous driving vehicles, Experience designing and implementing robust, reliable APIs for core geospatial or logistics services, Experience with performance tuning, reducing latency, and scaling critical backend systems, Proficiency with advanced debugging and visualization tools for analyzing location-based events and system behavior, Demonstrated background in refactoring large, complex backend services to improve system architecture, maintainability, and diagnostic capabilities, Expertise in developing systems for demand control, traffic shaping, or congestion management within a large-scale service environment, A background in machine learning pipelines, including feature engineering and integrating ML models into high-volume production environments
What You'll Do.
Collaborate with Machine Learning (ML) teams to integrate new location selection models to improve pin quality
Centralize critical location logic to ensure consistency and improve service reasoning
Design and implement scalable solutions for managing congestion
Develop and deploy demand control mechanisms to precisely manage Pick-up and Drop-off (PUDO) behavior across new operational areas
Build advanced tooling
and monitoring systems to debug and proactively identify customer pain points
How You'll Work.
Team & Collaboration
Collaborate with Machine Learning (ML) teams; collaborating with hardware and systems engineers
Full Job Description
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U. S. states. Software Engineering builds the brains of Waymo's fully autonomous driving technology. Our software allows the Waymo Driver to perceive the world around it, make the right decision for every situation, and deliver people safely to their destinations. We think deeply and solve complex technical challenges in areas like robotics, perception, decision-making and deep learning, while collaborating with hardware and systems engineers. If you're a software engineer or researcher who's curious and passionate about Level 4 autonomous driving, we'd like to meet you. The Pin Infrastructure team builds the infrastructure to ensure Waymo customers get picked up and dropped off at the right locations. As we rapidly expand, each new city introduces unique challenges that must be addressed to create a delightful user experience. In this hybrid role, you will report to an Engineering Manager. You will: Collaborate with Machine Learning (ML) teams to integrate new location selection models to improve pin quality. Centralize critical location logic to ensure consistency and improve service reasoning.•Design and implement scalable solutions for managing congestion. Develop and deploy demand control mechanisms to precisely manage Pick-up and Drop-off (PUDO) behavior across new operational areas. B
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