Waymo

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.

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.

You will: Partner with foundation model training teams to determine optimal data mixtures, training curricula, objectives, and other design choices that shape model capabilities. Design global-scale pipelines for dynamically updating and reusing data mixtures as our understanding of model behavior evolves and real-world datasets are continually ingested. Develop and deploy principled data-selection algorithms (e.g. influence estimation, proxy models, gradient similarity search) to find targeted subsets of data for fine tuning and RL.

You will: Own the data recipe for Waymo’s Foundation Model pre-training and post-training Lead and drive science on best practices around clustering, filtering, de-duplication, long-tail data mining, memorization, etc. Tech-lead a team of research engineers to build the data flywheel to enable the above from Waymo’s massive driving data Integrate emerging research from the broader community to do rigorous ablations and promising data research techniques. This includes scaling ladders for pre-training, data mix optimizations and RL recipes (preferences) for post-training.

You will: Build and operate the petabyte-scale data systems and ML pipelines at the heart of Waymo's foundation model development Shepherd cutting-edge foundation models from research prototypes to robust components within the Waymo Driver Create the automated infrastructure for rigorously benchmarking, continuously monitoring, and safely releasing models Wield large-scale compute and frameworks like Flume and JAX to process massive datasets and train/deploy complex models Drive significant leaps in the speed, reliability, and efficiency of the end-to-end ML development lifecycle Partner with AI Foundations, ML, and Platform experts to transform model innovations into tangible on-road improvements You have: Masters degree in Computer Science, Machine Learning, Robotics, similar technical field of study, or equivalent practical experience Proficiency in Python Proficiency in C++ Familiari

You will : Conduct comprehensive experimentation to train and deploy state-of-the-art Multimodal LLMs and World models to perform 3D Perception using sensor information from Camera, LiDAR and Radar. Write high quality code, unit tests, and documentation Collaborate effectively with partner and customer teams to deploy models to production Develop and maintain scalable data pipelines for Training & Eval to process data from multiple sources. Design and implement evaluation frameworks for perception models. Implement efficient training & inference optimization methods to maximize throughput Hands-on experience with Transformer architectures with in-depth knowledge on training ablations.

You will : Conduct comprehensive experimentation to train and deploy state-of-the-art Multimodal LLMs and World models to perform 3D Perception using sensor information from Camera, LiDAR and Radar.. Partner effectively with engineering and research teams across Waymo to deploy new models, and implement efficient workflows for model development and continuous training on new front-filled data. Apply and develop techniques such as quantization, pruning, knowledge distillation, and efficient attention mechanisms. Develop and maintain scalable data pipelines for Training & Eval to process data from multiple sources.

You will: Work with researchers and architects to translate high level requirements into hardware features Specify and design microarchitectures to deliver world class ML performance Perform power, area and performance exploration and optimization of digital ASIC designs Design high performance execution units, arithmetic circuits and programmable engines Work with verification teams to guarantee functional correctness and performance You have: BS degree in Computer Engineering or equivalent practical experience 5+ years of industry experience with SystemVerilog, ASIC RTL design and microarchitecture 3+ years designing and specifying microarchitectures of high performance computing cores (CPU/GPU/NPU) Fluency in at least one high level programming language such as Python, C++ We prefer: Experience designing datapath elements of high performance cores (CPU/GPU/NPU) Experience working with