Oversee enterprise audit activities to ensure partner conformity with Waymo standards and legal requirements. Collaborate with partners to address compliance issues and implement effective corrective action plans.
You will drive the strategy and technical implementation of complex safety triage workflows while partnering with engineering to deploy machine learning and generative AI models. Additionally, you will serve as a subject matter expert for human-in-the-loop systems and define policies to support the organization's scaling needs.
You will identify, negotiate, and implement strategic partner agreements while building relationships with executive stakeholders to support global market expansion. Additionally, you will develop internal systems and comprehensive partnership plans to drive Waymo's commercial deployment and business objectives.
Lead and mentor a high-caliber engineering team to architect and evolve the Fleet Orchestration Core systems. Drive the technical vision and strategy for the centralized platform managing offboard driving behavior for Waymo's autonomous fleet.
Lead the disruption management strategy and act as the Lead Incident Commander for high-severity, cross-functional events to ensure rider safety and fleet resilience. Orchestrate operational roll-outs, maintain playbooks, and deliver real-time executive briefings on complex incidents.
Lead the end-to-end ML data lifecycle, including mining, curation, and the development of scalable labeling policies for autonomous vehicle domains. Orchestrate cross-functional programs to design evaluation frameworks and metrics that drive model performance and ROI.
Build and operate scalable machine learning systems and simulation workflows to evaluate autonomous driving behaviors. Design large distributed systems covering the ML lifecycle, from planet-scale dataset generation to model training and evaluation.
Build and maintain efficient sensor simulators to evaluate the safety of autonomous driving models. Manage the rendering engine and the pipeline that allows internal customers to run simulations at scale.
Analyze and optimize generative model architectures to identify bottlenecks in training and inference performance. Design high-throughput serving solutions and implement model compression techniques to improve scalability and efficiency.
Lead the architectural design and development of Agentic AI components and scalable workflows to automate event triage for the Waymo Driver. Collaborate with cross-functional teams to integrate autonomous agents into the evaluation lifecycle and drive the technical roadmap.
Lead the Enterprise Outsourcing & Services vertical to design and scale Waymo's global external workforce architecture across Engineering, Operations, and Corporate functions. Manage a $100M+ portfolio, cultivating strategic supplier alliances and implementing outcome-based commercial models.
Lead technical efforts and define roadmaps while collaborating across cross-functional teams including PM, UX, and legal. Manage people and drive the completion of complex engineering efforts for autonomous driving technology.
Design and optimize VLM/LLM model architectures to align with hardware constraints for on-device use cases. Collaborate with research, software, and hardware teams to deliver end-to-end perception solutions for autonomous driving.
The specialist bridges the gap between simulation software and real-world execution to ensure the safety and quality of the Waymo Driver. Key duties include optimizing simulation tools, driving rapid-response testing for field issues, and developing operational policies for AI/ML workflows.
Lead the software architecture and infrastructure for onboard model consolidation across various subsystems in autonomous driving. Design frameworks for efficient model integration and inference while aligning data generation between training and production.
Lead the design and deployment of evaluation approaches to assess the realism of multimodal world models and generative systems. Architect scalable machine learning pipelines and discriminator models to improve simulator realism for autonomous driving.
Own the C++ server infrastructure and concurrent data streaming pipelines for the Webviz platform. Design abstractions to process fleet logs and build APIs for automated evaluation pipelines to analyze driving data.
Lead the Enterprise Outsourcing & Services vertical to define the future of work by leveraging global external ecosystems for engineering and hardware scaling. Develop procurement strategies for R&D hardware and engineering services while managing complex contracts and vendor relationships.
Design and optimize large-scale continual pre-training pipelines for VLM foundation models. Conduct research on integrating multimodal data streams and develop metrics to evaluate model performance in autonomous driving contexts.
The role focuses on software quality operations to support the development of the Waymo Driver. It involves ensuring the reliability and safety of autonomous driving technology across various platforms.
Lead end-to-end procurement and category strategy for Marketing, Communications, PR, and Public Affairs. Design agency architecture and negotiate complex commercial models to scale the brand globally while minimizing business risk.
Partner with Engineering to deploy ML and Gen-AI tools for issue discovery and quality assurance of the Waymo Driver. Define technical policies and SOPs to integrate AI insights into vendor workflows and operational execution.
Partner with Engineering to deploy ML and Gen-AI tools for issue discovery and quality assurance of the Waymo Driver. Define technical policies and SOPs to integrate AI insights into vendor workflows and operational execution.
Partner with Engineering to deploy ML and Gen-AI tools for issue discovery and quality assurance in autonomous driving. Define technical policies and SOPs to integrate AI insights into vendor workflows and operational execution.
Lead the development of scalable AI/ML infrastructure for multi-billion parameter foundation models used in autonomous vehicle simulations. Collaborate with global teams to improve simulation realism and mentor junior engineers on architectural decisions.
Develop importance sampling techniques and machine learning models to maximize the statistical efficiency of discovery pipelines for rare autonomous driving events. Collaborate with cross-functional teams to deliver evaluation products and maintain high code health standards in a complex codebase.
Lead the ML Evaluation team to define the strategic vision for evaluation platforms and infrastructure. Manage and mentor engineers while collaborating cross-functionally to validate next-generation deep neural networks.
Develop evaluation frameworks and metrics to ensure the safety and quality of autonomous vehicle performance and simulation. Collaborate with engineering and product teams to solve ambiguous data problems and facilitate deployment readiness.
Develop evaluation frameworks and metrics to ensure the safety and quality of autonomous vehicle performance and simulation. Collaborate with engineering teams to solve ambiguous problems and communicate data-driven conclusions to senior stakeholders.
Design and optimize Angular applications to build mission-critical tools for Waymo's Fleet Monitoring systems. Collaborate with Product and UX teams to develop internal user-facing products and scalable platform functionalities.
Lead the development of cutting-edge deep learning and Gen AI models to analyze autonomous vehicle behavior and automate high-volume workflows. Collaborate with cross-functional teams to define technical strategy and optimize ML models for fleet-wide evaluation.
Implement and scale Waymo's core trip platform to support ride-hailing and delivery use cases for internal and B2B partners. Design partner-facing API services to manage trip requests, calculate ride times, and determine pricing.
Implement and scale Waymo's core dynamic pricing engine using ML models and optimization algorithms to balance supply and demand. Build infrastructure for pricing experimentation and monitoring to maximize fleet profitability and service competitiveness.
Implement and scale the core economic engine for ride-hailing services, focusing on pricing, matching, and positioning. Develop infrastructure for automatically training and deploying sophisticated ML and optimization models.
The role involves partnering with engineering teams to design and deploy machine learning models for issue detection and quality assurance. Additionally, it includes developing data-driven strategies and ensuring the integration of AI tools into operational workflows.
You will partner with Engineering to design, test, and deploy cutting-edge Machine Learning and Generative AI models to improve issue discovery and quality assurance. Additionally, you will serve as the key link between AI/ML development and operational execution, defining new policies and quality control processes.
