Frontier Tech Foundation Model Pearl Jobs

Implement, optimize, and build novel foundation models from the initial research prototypes to high-performance production models.

Waymo’s Foundation Model pre-training and post-training Lead and drive science on best practices around clustering, filtering, de-duplication, long-tail

At Applied Intuition, you will: Conduct research on pretraining world-action foundation model with various world modalities

modeling tasks Research contribution and efficiency of different modalities in a multi-modal Foundation Model Explore and apply training data

AI Foundations areas that we are currently focusing on include reinforcement learning, learning from demonstration, generative modeling, Bayesian inference, hierarchical

We advance the state of the art in molecular design by training large-scale foundation models that enable cutting-edge generative approaches.

We are pioneering the use of large multimodal foundation models (e.g., Gemini) to build a powerful offboard reasoning and data flywheel system.

with research and engineering teams to improve Waymo’s foundation models Conduct cutting-edge research and potentially communicate research findings to

related topics including 3D/world-action foundation model, multi-modal pretraining, feed-forward Gaussian splatting, world foundation model with

(e.g., diffusion, flow matching, RL, foundation model architectures and training methods).

Our models sit at the core of this effort, bridging cutting-edge foundation model techniques with real-world robotic execution.

(LLMs), vision language models, generative AI, diffusion models, large-scale model training, data labeling, data generation and packaging for model training

large-scale model training, foundation models, model parallelism, multi-node training Experience with bio sequence data and datasets — various genomic and

model startups, advanced robotics institutes, or high-tier academic research groups focusing on physical AI, foundation video models, or world simulation.

To increase the fidelity and steerability of our simulations, we employ the latest ML technologies such as large foundational World Model trained on our