Magic’s mission is to build safe AGI that accelerates humanity’s progress on the world’s most important problems. We believe the most promising path to safe AGI lies in automating research and code generation to improve models and solve alignment more reliably than humans can alone. Our approach combines frontier-scale pretraining, domain-specific RL, ultra-long context, and inference-time compute to achieve this goal.

About the role

As a Research Engineer, you’ll work on training, evaluating, and serving large AI models and new inference-time compute techniques, build internet-scale datasets, and help prototype new research and product ideas.

What you'll work on

• Optimize inference throughput for novel model architectures

• Contribute to frameworks used for our research and production workloads

• Train trillion-parameter models on large GPU clusters

• Curate post-training datasets to improve targeted capabilities

• Build out internet-scale data pipelines and crawlers

• Design, prototype, and optimize new model architectures

• Contribute to research acro