Applied Scientist

Applied Scientist focuses on build the reference implementations that let other teams deploy compressed models without our help.

What the role involves

• Build the reference implementations that let other teams deploy compressed models without our help.
• Design recovery strategies grounded in the model's actual structure.
• Build evaluation methodology that makes accuracy, latency, memory, and cost trade-offs explicit.
• You pick up a vision-language model whose vision tower needs to fit tight memory, latency, and cost budgets for deployment.
• You design a healing run to close the gap, tuning the data mix and training objective to fine-tune the compressed model back toward the teacher's quality.
• A typical week mixes hands-on compression and evaluation with design discussions alongside fellow scientists and platform engineers.

Skills and requirements

• Master's degree, or a PhD and experience in CS, CE, ML or related field.
• Experience programming in Java, C++, Python or related language.
• Experience in patents or publications at top-tier peer-reviewed conferences or journals.
• Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning.

Additional role context

• Our compression platform delivers 20x to 100x neural network compression, but using it well still takes weeks of hands-on learning and expert intuition.
• We compress frontier models 20x to 100x and put them in the hands of millions of customers, everywhere from your pocket to the cloud: the device in your hand, the Echo on your coun.
• If you want your science in real products at real scale, and you want to put the frontier of generative AI in the hands of millions of customers, come build it with us.