Periodic is hiring SWE's for physics simulations, scientific data, and lab robotics These are hard problems that codex/cc can't one-shot, because they require interfacing with the real world and collaborating with scientists Science experience is a + but not required! Apply ⬇️

Another Neon infra tidbit: @periodiclabs accelerated checkpoint conversion ~30x down to just 1 minute, helping us deploy faster to get rapid feedback from our labs. Our models train in Megatron, but SGLang inference consumes weights in HuggingFace format. Traditionally, conversion ran serially: 1. rebuild the entire checkpoint from individual weight tensors 2. convert the checkpoint 3. reshard it to be inference-ready This could take 30 min for a trillion parameter model! Noticing that conversion shouldn't require materializing the full checkpoint, @hsu_byron introduced Fast Resharding: 1. parallelize conversion across Ray actors 2. convert expert chunks directly instead of assembling the full expert tensor in memory We upstreamed Fast Resharding to Miles in PR #1371#. Now even you can deploy trained models to production in a matter of minutes.

You saw the AI & science. Let's talk about the RL infra it took to build @periodiclabs Neon. To minimize training-inference mismatch in RL, SGLang captures inference's MoE routing decisions for each rollout and we "replay" them while training. In agentic (multiturn tool-use) settings, SGLang exports these router decisions in response to each decoding request, i.e. after each conversation turn. So when *any* data-parallel rank finishes a conversation turn, *all* other ranks must wait until routing data finishes exporting. This slowdown is exacerbated because we export routing decisions from the *entire* conversation rather than just the most recent turn! When @hsu_byron @vwxyzjn discovered this in our Kimi K2 RL setup, they introduced Delta Router Replay: cache previous turns' router decisions on the training client, so you can export only the delta (most recent turn's router decisions) upon each decoding request. Delta Router Replay significantly speeds up our long-context agentic RL runs, and @hsu_byron upstreamed it to SGLang (#24851#) a few months ago.

Watch Neon investigate a real sample from our superconductor lab It hypothesizes about crystal structure, reasons about synthesis conditions, and iterates with tools until it finds a physically realistic solution More and more of science will look like this in coming years