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The Site Reliability Engineer at Waymo will design and architect cloud systems for reliability and scalability. They will implement monitoring systems, manage incident responses, and develop automation tools. A focus on security best practices and system performance analysis is essential.
In this role, you will develop and implement long-term strategies for infrastructure scalability, manage operational requirements, lead projects for process improvements, resolve technical issues, and collaborate with engineering and product teams for operational readiness.
In this role, you will apply sensor fusion and machine learning techniques to solve real-world challenges. You will develop and deploy machine learning models, including vision language models (VLMs), and create data mining, labeling, training, and evaluation pipelines. Collaboration with product, infrastructure, and research teams is key to advancing the efforts in perception ML and VLMs.
The Software Engineer will collaborate with application teams to optimize GPU algorithms, improve compiler optimizations, analyze performance, and contribute to hardware design for autonomous vehicles. This role requires extensive experience in C++ programming, GPU optimization, and performance analysis.
The Senior Business Intelligence Engineer will develop reporting infrastructure, create scalable data pipelines, enhance data sets with third-party data, and maintain financial systems. They will collaborate with multiple departments to ensure accurate reporting and build a self-service data function to enhance data literacy within the organization.
The Escalation Manager will be responsible for managing emergency calls, providing situational guidance during incidents, and leading technical decisions. This role involves coordinating emergency responses, facilitating process improvements, and ensuring effective communication between teams and emergency responders.
The Group Product Manager will lead a team in developing strategies and managing the release process of a simulator for autonomous vehicles, focusing on safety and evaluation methodologies. This role involves market expansion, enhancing simulator capabilities, and ensuring realistic vehicle simulation performance.
As a Strategic Partner Development Manager at Waymo, you will negotiate unique agreements and execute a strategy to deepen partnerships with utilities, enhancing Waymo's charging infrastructure. Your role includes cultivating relationships with executive partners and collaborating with cross-functional teams to drive business initiatives. You'll represent Waymo at industry conferences and help define commercial deployment strategies.
Manage Waymo's extended workforce access program by leading projects to mitigate risks, ensuring compliance with security policies, and implementing access control measures. Collaborate with technical teams to gather requirements, conduct risk assessments, and strengthen security processes. Develop training materials, automate reporting, and communicate updates effectively.
In this hybrid role, you will shape the marketing strategy for Waymo's products, focusing on user insights and collaboration across teams to enhance product launches and brand perception. You will lead initiatives to position products effectively and drive campaigns that resonate with consumers, while also refining creative ideas into actionable plans.
As a Payroll Accountant, you will manage month-end payroll accounting, resolve payroll issues, automate existing processes, and oversee new entity payroll setups. Your work will contribute to the overall financial health and compliance of Waymo.
As a Staff Machine Learning Engineer at Waymo, you will advance ultra-realistic autonomous vehicle simulations by applying your expertise in machine learning, especially generative AI. You will manage product innovations from prototyping to scaling simulations and collaborate closely with a team to implement production-ready solutions.
As a Software Engineer in the Perception team, you'll design systems for deploying deep learning models on Waymo vehicles, enhance onboard infrastructure, and optimize existing systems for scalability and clarity. You'll collaborate with teams to innovate perception solutions that improve vehicle safety and performance.
As a Software Engineer in Machine Learning/Computer Vision at Waymo, you will apply machine learning to build multi-modal sensor fusion architectures, design large-scale foundation models, and develop data mining, labeling, training, and evaluation pipelines. You will collaborate with research teams and tackle real-world problems.
You will lead an applied ML team focused on generative AI simulation solutions, guide product innovation, and develop engineers in a collaborative environment, ensuring alignment with product goals and managing project execution.
As a Systems Engineer at Waymo, you will collaborate with cross-functional teams to define system requirements and analyze data for system evaluation. Your role includes creating documentation, leading discussions on system design, and driving alignment across teams to ensure safety and regulatory compliance.
The Technical Lead Manager will lead a team focused on building and maintaining scalable infrastructure for simulation-based evaluation of the Waymo Driver. Responsibilities include managing a small team of software engineers, developing production-grade code, and setting the technical vision and strategic direction for the team and the organization.
You will work with a creative team on bringing up new hardware platforms and developing software and machine learning methods to improve performance. You will also build tools to evaluate new platforms against existing ones.
As a Machine Learning Hardware Engineering intern at Waymo, you will develop co-simulation methodologies for ML accelerator pipelines, explore automated testing generation, and optimize simulator performance while gaining knowledge of ML accelerator microarchitecture.
As a Senior Backend Software Engineer on the Simulator Team, you will develop backend systems for synthetic data generation, collaborating with ML engineers and data scientists to enhance data pipelines and infrastructure capabilities. Your focus will be on creating high-fidelity datasets and scalable services for autonomous vehicle development.