28 days ago
Palo Alto, CA, USAStaff+
Base Salary
$274k - $292k/yr
Responsibilities
- Lead the design, development, and deployment of world models and generative systems for realistic and controllable sensor generation in large-scale autonomous-system simulation.
- Develop generative pipelines for high-fidelity synthetic datasets using multimodal models, diffusion techniques, and world models.
- Partner with research teams across Alphabet to integrate advanced modeling techniques.
- Lead sim-to-real efforts using domain adaptation and transfer learning to match simulated behavior with physical on-vehicle systems.
- Apply VLMs to improve the understanding and controllability of world simulation products.
- Shape organization-wide AI infrastructure, workflow management for large-scale training, foundational AI initiatives, testing frameworks, and ML model evaluation.
Requirements
- 12+ years of experience developing and designing machine learning applications, autonomous systems, or simulation platforms.
- B.S., M.S., or Ph.D. in Computer Science, Machine Learning, Robotics, or a related field, or equivalent practical experience.
- Demonstrated ability to lead significant, complex ML projects from research through production-ready solutions.
- Deep expertise in 3D world modeling or 3D computer vision.
- Familiarity with 3D reconstruction and rendering techniques such as 3D Gaussian Splatting.
- In-depth knowledge of generative AI, predictive world models, autoregressive models, or self-supervised learning from multimodal sensor streams.
- Hands-on experience with sim-to-real transfer, domain adaptation, and world models.
- Experience developing testing frameworks and evaluating ML models for edge cases and rare events in complex systems.
Benefits
- Hybrid work arrangement based in Palo Alto.
- Full-time position with bonus, equity, and benefits.
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