Research Engineer - AI Infrastructure

Job Summary

To support the development of frontier AI systems, the full-time Research Engineer - AI Infrastructure will build and optimize infrastructure for large-scale reinforcement learning (RL) and distributed training workloads, collaborating with researchers and engineers in a remote work environment.

Key responsibilities

• Build and optimize systems infrastructure for large-scale RL and distributed training workloads
• Improve end-to-end training efficiency across compute, memory, networking, and scheduling layers
• Design and implement low-level performance optimizations and contribute to open-source libraries for model training

Required qualifications

• Strong systems engineering experience in AI/ML infrastructure, particularly for large-scale model training or inference
• Deep familiarity with PyTorch and distributed training frameworks such as PyTorch Distributed and DeepSpeed
• Experience optimizing training performance across kernels, memory movement, and communication overhead
• Hands-on experience with large-scale training techniques including data parallelism and tensor parallelism
• Strong understanding of GPU architecture and performance debugging