4 hours ago
Responsibilities
- Architect and implement next-generation model architectures for frontier world models with research teams.
- Design and iterate on real-world evaluation pipelines to measure and accelerate model capabilities.
- Develop model distillation and optimization techniques for real-time serving at global scale.
- Build scalable data ingestion pipelines and automated filtering mechanisms to improve training quality and benchmark performance.
- Maintain robust, scalable codebases and collaborate across modeling, data, evaluation, research, and product teams.
Requirements
- Bachelor’s degree or equivalent practical experience.
- At least 5 years of experience developing, training, and deploying diffusion models and generative video architectures.
- Experience writing custom GPU/TPU kernels for model serving, such as with JAX or PyTorch.
- Preferred: PhD in Computer Science, Machine Learning, AI, or a related quantitative field, or equivalent practical experience.
- Preferred: experience in frontier AI research labs, particularly pre-training or post-training teams.
- Preferred: proficiency writing TPU/GPU custom kernels to optimize model performance and inference.
- Preferred: track record deploying machine learning models to production at scale or publishing widely adopted open-source research.
Tech Stack
Categories
AI ResearchML Engineering
About Google
A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone. Check out our career opportunities at goo.gle/3DLEokh