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The Research Engineer will design, optimize, and scale systems for large AI models, enhancing performance, reliability, and efficiency in model inference and deployment.

Design and optimize large-scale distributed training infrastructure, focusing on numerical methods to enhance efficiency and stability in AI model training.

The role involves designing and optimizing distributed training systems for large models to enhance research efficiency and productivity in AI.

The Software Engineer, Data Infrastructure will design scalable systems for data processing and orchestration, collaborating with teams to enhance data quality and accelerate research.

Develop and maintain full stack applications focusing on APIs, UX, system reliability, security, and collaboration across teams.

Design, build, and operate GPU supercomputing environments, automate large GPU clusters, and collaborate with researchers to optimize performance and resources.

Design and build infrastructure for scalable reinforcement learning, optimize RL training pipelines, and collaborate with researchers on production-grade solutions.

As an Infrastructure Research Engineer, you'll design and implement systems for scaling Tinker, optimizing GPU utilization, and developing frameworks to improve performance while collaborating with researchers and developers.

The role involves designing and optimizing ML kernels for large-scale language model training, collaborating on algorithmic design, and enhancing compute efficiency.

As a Software Engineer, you'll develop and maintain systems for AI models, enhance infrastructure, and collaborate across teams on product development.