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Waymo’s Software Quality Operations Specialist in London designs and deploys AI/ML tools to detect autonomous vehicle issues, triage driving events, and scale operations for new international markets like London.
Develops and maintains AI-driven quality assurance processes for Waymo’s autonomous driving software, analyzing driving events and deploying ML tools to ensure safety and scalability across new markets.
This role ensures the safety and reliability of Waymo's autonomous driving software by developing AI-powered quality control processes, analyzing driving events, and scaling operations for rapid expansion into new cities and vehicle platforms.
Develops and optimizes low-level Android Automotive software for an in-house vehicle infotainment system, integrating Linux kernels, AOSP, and hardware-specific components.
Lead a data science team to rigorously evaluate Waymo’s autonomous driving system’s compliance with road rules, using statistical methods and cross-functional collaboration to improve safety and scale deployment.
Leads the architecture and development of Waymo's iOS app, focusing on modular, performant SwiftUI/Swift codebases, networking, and user-facing features for autonomous ride-hailing services.
Builds and scales machine learning infrastructure for autonomous vehicle perception systems, focusing on data flywheels, model training, and performance evaluation using large-scale real-world driving data.
Leads development of deep learning and generative AI models to evaluate and improve Waymo’s autonomous driving systems, using large-scale data and ML frameworks like TensorFlow and PyTorch.
Build ultra-realistic autonomous-vehicle simulations using large foundation models to train and evaluate Waymo’s self-driving AI in London, collaborating with teams in Mountain View and Oxford.
Leads the design and implementation of evaluation systems for large vision and language models used in autonomous driving, building benchmarks to assess model quality, safety, and realism.
Leads the design and scaling of AI/ML infrastructure for billion-parameter foundation models used in ultra-realistic autonomous-driving simulations, collaborating with research teams to improve simulation fidelity.
Builds and scales core infrastructure for Waymo’s autonomous ride-hailing and fleet systems, collaborating across teams to deliver mission-critical tools and services.
Leads the development of a simulation-based fault-detection system for Waymo’s autonomous driving software, ensuring reliability through large-scale distributed testing and ML-driven analysis.
Designs and builds privacy systems for autonomous vehicles, ensuring GDPR compliance through anonymization, data pipelines, and access controls while collaborating with legal and engineering teams.
Staff Software Engineer at Waymo designing and leading evaluation frameworks for autonomous driving simulation, blending C++/Python systems with AI-driven virtual environments to validate realism.
Develops backend systems and APIs to improve autonomous ride-hail services, focusing on rider experience in complex venues and operational data analysis for Waymo’s fleet.
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…
Leads cross-functional planning to maximize utilization of autonomous-driving simulation compute resources, balancing trade-offs and driving decisions for Waymo’s global deployment teams.
Engineer safety systems for autonomous vehicles, performing hazard analyses, defining safety requirements, and guiding design decisions to ensure compliance with regulations and industry standards.
Leads a backend engineering team to build and maintain high-performance data pipelines for autonomous vehicle simulation and real-world performance analysis, using C++, Python, and SQL.
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