Build and optimize secure, scalable distributed systems for AI research, focusing on sandboxed execution, performance, and resource management.

Design and build optimized solutions for AI workloads on supercomputing infrastructure, troubleshoot large-scale GPU deployments, and enhance system usability and reliability.

As a Distributed Systems Engineer, you will build data systems for ultra-long context inference, focusing on performance, availability, and troubleshooting across various environments.

As a Kernel Engineer, design and maintain high-performance kernels, optimize training and inference performance, and evaluate compute kernels for alternative hardware.

As a research engineer, you'll train and evaluate large AI models, optimize inference throughput, and build data pipelines to enhance research and production workflows.

Develop and maintain data pipelines for gathering post-training datasets, ensuring data quality and efficiency in processing and generation.

As a Technical Sourcer, you'll identify and attract exceptional tech talent, manage candidate pipelines, and design sourcing strategies in AI and engineering.

Contribute to building safe AGI through automating research and code generation, enhancing models, and aligning with team values.

Lead the development of internal tools and infrastructure to enhance productivity for the pre-training data team, focusing on developer experience and best practices in code organization.

As a Software Engineer, build and maintain product surfaces that integrate with AI technology, collaborating with design and research teams.