RL Infrastructure Engineer – Frontier-Scale Systems

Prime Intellect, Inc.; San Francisco (CA); Remote; USD 150,000 - 350,000; Full time

Benefits offered by this job

Remote work option

Visa sponsorship

Relocation assistance

Team off-sites & conferences

Job summary

Prime Intellect, Inc. is building the open frontier AI infrastructure stack for frontier-scale model training, evaluation, and deployment. Our Lab platform unifies compute, environments, sandboxes, and high-performance training for SFT, RL, tool use, and production models.

The role focuses on improving end-to-end training efficiency, designing low-level optimizations, and advancing distributed training across data, tensor, and pipeline parallelism, in collaboration with researchers and engineers.

Qualifications

• Strong systems engineering experience in AI/ML infrastructure, especially around large-scale model training or inference.
• Deep familiarity with PyTorch and distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP, Megatron, vLLM, Ray, or related tooling.
• Experience optimizing training performance across kernels, memory movement, communication overhead, or parallelization strategy.
• Hands-on experience with large-scale training techniques including data parallelism, tensor parallelism, and pipeline parallelism.

Responsibilities

• Improve end-to-end training efficiency across compute, memory, networking, and scheduling layers.
• Design and implement low-level performance optimizations, including kernels, communication paths, and runtime improvements.
• Work on distributed training systems spanning data, tensor, and pipeline parallel workloads.
• Help shape the architecture of our RL training stack, including async rollout and post-training systems.
• Contribute to open-source libraries and internal infrastructure used for frontier-scale model training.
• Collaborate closely with researchers and infrastructure engineers to translate bottlenecks into concrete systems improvements.

Skills

Systems engineering

AI/ML infrastructure

Distributed training

GPU architecture

Performance profiling

Data parallelism

Tensor parallelism

Pipeline parallelism

CUDA kernels

Triton kernels

Tools

PyTorch

PyTorch Distributed

DeepSpeed

FSDP

Megatron

vLLM

Ray

Job description

Prime Intellect, Inc. is building the open frontier AI infrastructure stack for frontier-scale model training, evaluation, and deployment. Our Lab platform unifies compute, environments, sandboxes, and high-performance training for SFT, RL, tool use, and production models.

The role focuses on improving end-to-end training efficiency, designing low-level optimizations, and advancing distributed training across data, tensor, and pipeline parallelism, in collaboration with researchers and engineers.