LLM Inference Engineer

Reposted 8 Days Ago
Hiring Remotely in Menlo Park, CA
In-Office or Remote
Mid level
Artificial Intelligence • Hardware • Information Technology • Robotics
From bits to atoms.
The Role
Integrate and optimize large-scale inference systems for AI research, supporting GPU utilization and low-latency access across models in a collaborative setting.
Summary Generated by Built In

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

Top Skills

Gpus
Large Language Models
Reinforcement Learning
Sglang
Tensorrt-Llm
Vllm
Am I A Good Fit?
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The Company
32 Employees
Year Founded: 2025

What We Do

We're building AI scientists and the autonomous laboratories for them to operate.

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