Build and scale generative world models and synthetic-data pipelines for autonomous driving, connecting model research to training-ready data and measuring its impact on driving models.
Build and operate production machine learning models that personalize the subscriber journey, improve conversion and retention, and support subscription products through scalable, measurable ML capabilities.
Build and deploy production-grade machine learning systems for client challenges, shaping scalable software architecture and deployment standards while advising stakeholders and collaborating across technical and commercial teams.
Develop and validate machine learning models and 3D reconstruction methods that improve simulated lidar, radar, and camera realism, helping close sim-to-real gaps in autonomous vehicle systems.
Bring up machine learning models on AI accelerators, develop MLIR lowering paths, validate numerical correctness, and optimize inference performance across models, compilers, kernels, and runtimes.
