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LLM Inference Engineer

Periodic Labs

Menlo Park, California, USA permanent

Posted: September 24, 2025

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Quick Summary

We are looking for a skilled LLM Inference Engineer to join our team and contribute to the development of state-of-the-art models for AI scientific research. The ideal candidate will have expertise in building and maintaining high-performance serving infrastructure for large language models, with a strong background in AI and physical sciences. The successful candidate will be an owner of the team, with a passion for solving complex problems and pushing the boundaries of scientific discovery.

Job Description

About Periodic Labs

We are an AI + physical sciences lab building state of the art models to make novel scientific discoveries. We are well funded and growing rapidly. Team members are owners who identity and solve problems without boundaries or bureaucracy. We eagerly learn new tools and new science to push forward our mission.

About the role

You will integrate, optimize, and operate large-scale inference systems to power AI scientific research. You will build and maintain high-performance serving infrastructure that delivers low-latency, high-throughput access to large language models across thousands of GPUs. You will work closely with researchers and engineers to integrate cutting-edge inference into large-scale reinforcement learning workloads. You will build tools and directly support frontier-scale experiments to make Periodic Labs the world’s best AI + science lab. You will make contributions to open-source LLM inference software.

You might thrive in this role if you have experience with:

• Optimizing inference for the largest open-source model

• High-performance model serving frameworks such as TensorRT-LLM, vLLM, SGLang

• Distributed inference techniques (tensor/expert/pipeline parallelism, speculative decoding, KV cache management)

• Optimizing GPU utilization and latency for reinforcement learning

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