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Senior/Staff ML Engineer at Waymo building ultra-realistic 3D/4D world models and generative systems for autonomous vehicle simulation using advanced ML techniques like diffusion models and VLMs.
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.
Builds and maintains ML tooling and infrastructure to monitor model performance and diagnose issues for Waymo's autonomous driving software stack.
Designs and deploys real-time dynamic pricing algorithms for an autonomous ride-hailing marketplace, balancing supply, demand, and profitability using ML and distributed systems.
Senior engineer building ML infrastructure for Waymo's ride-hailing marketplace—scaling the economic engine and automating ML model training, deployment, and inference for real-time pricing, matching, and routing decisions. Core tech includes Java/C++, Python, TensorFlow/PyTorch, and large-scale backend systems.
Builds and scales machine learning infrastructure for autonomous vehicle perception systems, focusing on data flywheels, model training, and performance evaluation using large-scale real-world driving data.
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.
Develops and optimizes machine learning models for autonomous vehicle perception systems, using large-scale sensor data and frameworks like PyTorch or JAX.
Build ultra-realistic autonomous-vehicle simulations using large foundation models to train and evaluate Waymo’s self-driving AI in London, collaborating with teams in Mountain View and Oxford.
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.
Leads the design and scaling of AI/ML infrastructure for billion-parameter foundation models used in ultra-realistic autonomous-driving simulations, collaborating with research teams to improve simulation fidelity.
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.
Leads a team developing machine learning models to evaluate and improve autonomous vehicle behavior using deep learning, Gen AI, and large-scale simulation systems.
Senior ML engineer at Waymo building and evaluating AI-driven simulation systems to validate realism of autonomous driving scenarios using generative models and multimodal evaluation tools.
Designs and optimizes large vision-language and language models for autonomous driving, focusing on hardware-aligned architectures and on-device performance in a safety-critical environment.
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 improves machine learning models to generate high-fidelity simulation data for autonomous driving, focusing on realistic agent behavior and sensor accuracy.
Develops and deploys machine learning models to evaluate autonomous vehicle behavior in simulation and real-world settings using Python/C++ and deep learning.
Builds and evaluates machine learning models for autonomous vehicle simulations, focusing on realism metrics and integrating foundation models into Waymo's evaluation systems.
Lead the design and deployment of auto-labeling systems and computer vision models to scale data pipelines for autonomous driving, using C++, Python, PyTorch, and TensorFlow.
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