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Lead the design and development of machine learning systems to evaluate and improve Waymo's autonomous driving technology, focusing on reinforcement learning, generative models, and large-scale simulation workflows.
Develops AI-driven automation for autonomous vehicle sensor maintenance and fleet operations, using machine learning and robotics to improve efficiency in a hybrid work environment.
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.
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.
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.
Senior ML Engineer builds and deploys computer vision and vision-language models to generate high-fidelity labels for autonomous driving, using deep learning, generative AI, and reinforcement learning at scale.
Develops and maintains petabyte-scale data systems and ML pipelines for autonomous driving foundation models using frameworks like JAX and Flume/Beam.
Develops and deploys machine learning models to evaluate autonomous vehicle behavior in simulation and real-world settings using Python/C++ and deep learning.
Build and scale large vision-language foundation models for autonomous driving, using multimodal pre-training and reinforcement learning to improve scene understanding and autolabeling.
Build and operate petabyte-scale ML pipelines and infrastructure to train, benchmark, and deploy foundation models for Waymo’s autonomous driving systems using frameworks like JAX and Flume.
Build and deploy multimodal LLMs and world models for 3D perception in autonomous vehicles using camera, LiDAR, and radar data.
Develops and deploys machine-learning recipes for autonomous-driving agents, working with large-scale data, evaluation pipelines, and foundation models to improve safety and realism.
Develops AI foundation models for autonomous driving, integrating large-scale systems with production platforms and adapting models to new sensors/platforms while collaborating across Alphabet teams.
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