• Provide Customer with overview of installation activity, site-specific information and access to appropriate contacts. • Handle Customer-relation problems promptly and appropriately, provide guidance, escalate issues according to established procedures. • Provide software service, pre-sales, post-sales or service delivery support. • Deliver services, including customized services to large enterprise, complex or corporate accounts. • Use proactive monitoring procedures/tools to identify problem prevention opportunities.

• Serve as the Tier 3 escalation point for complex desktop and endpoint support issues. • Troubleshoot and resolve advanced Windows desktop, Microsoft 365, and endpoint management issues. • Provide technical leadership and mentorship to Desktop Support engineers, assisting with escalated incidents and knowledge transfer. • Support and administer Microsoft endpoint technologies including Microsoft 365, Active Directory, Intune, Windows Autopilot, and Microsoft Entra ID. • Manage endpoint provisioning, configuration, deployment, and lifecycle management. • Assist with endpoint security, device compliance, software deployments, and policy management. • Work collaboratively with infrastructure, security, and application teams to resolve cross-functional issues. • Document technical solutions, standard operating procedures, and best practices.

• Provide technical support in infrastructure services, responding to issues and assisting in tasks. • Contribute to the implementation of infrastructure projects and assignments. • Monitor and troubleshoot infrastructure systems, ensuring reliability and performance. • Work with the team to enhance infrastructure effectiveness and address technical challenges. • Support the development of infrastructure documentation, including incident logs and configuration records. • Apply technical knowledge to address infrastructure-related challenges. • Follow established best practices and standards in infrastructure service delivery. • Utilize technical skills to address infrastructure issues and incidents.

Role Description The Simulator Team at Waymo builds state-of-the-art simulations of realistic environments for testing, training, and validation of the Waymo Driver. Our team is a diverse, and collaborative group of machine learning (ML) engineers, software engineers, and ML research engineers. We develop industry-leading simulation solutions using advanced generative and reconstructive ML algorithms, to model the real world, encompassing realistic agents, roads, traffic systems, weather, and the full sensor suite (Camera, Lidar, Radar). To accelerate the fidelity, scalability, controllability, and richness of our simulations, we are pushing the frontiers of 3D world modeling. We leverage state-of-the-art ML technologies trained on large-scale datasets to create dynamic and semantically rich virtual worlds, directly impacting the development and validation of the Waymo Driver. In this role, you will report to a Senior Staff Engineering Manager. You will: - Analyze model architectures and identify bottlenecks in training and inference performance (e.g., memory bandwidth, compute, communication). - Apply and develop techniques such as quantization (e.g., FP8, INT4), pruning, knowledge distillation, and efficient attention mechanisms. - Optimize model code for specific hardware accelerators (TPUs, GPUs), leveraging compiler features and low-level libraries (e.g., XLA). - Experiment with different model partitioning and sharding strategies (e.g., data, tensor, pipeline parallelism, expert parallelism) to improve scalability and efficiency. - Design and implement low-latency, high-throughput serving solutions for generative models and optimize training pipelines to reduce training time. - Build and maintain tools for performance analysis, profiling (e.g., xprof), and debugging of ML models. Qualifications - MS or PhD in Computer Science, Machine Learning, Robotics, or a related field. - 5+ years of experience with deep learning architectures (especially Transformers, Diffusion Models, MoEs), algorithms, and optimization techniques. - Proficiency in JAX, Flax, and potentially TensorFlow/PyTorch. - Expertise in using profiling tools (e.g., XProf, Perfetto, NVIDIA Nsight) to diagnose performance issues in ML workloads. - Hands-on experience with quantization, pruning, distillation, and other model compression methods. - Strong programming skills in Python and potentially C++, with experience in software development best practices. Requirements - Knowledge of TPU and GPU architectures and how to optimize code for them. - Familiarity with ML compilers like XLA and an understanding of how they translate high-level code to efficient hardware instructions. - Understanding of concepts related to training and serving models across multiple devices and machines. - Experience contributing to frameworks and libraries that improve training speed and scalability (e.g., JAX, Gemax, XManager). Benefits - Waymo employees are eligible to participate in Waymo’s discretionary annual bonus program. - Equity incentive plan. - Generous Company benefits program, subject to eligibility requirements. Salary Range The expected base salary range for this full-time position across US locations is $251,000 — $310,000 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.