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Member of Technical Staff (Infrastructure Engineer, Training and Inference Systems)

inherent· Technical Staff
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LondonFull-timePosted 5mo ago

About the role

Infrastructure engineer focused on building and maintaining training and inference systems for large-scale RL and AI research at Inherent. Emphasis on speed, reliability, and ease-of-use for distributed training/inference in scientific domains, with close collaboration with core research.

Responsibilities

  • Contribute to our training + inference infrastructure end-to-end.
  • Build systems to run large-scale experiments: distributed job orchestration, data pipelines, evals.
  • Implement and harden RL and post-training libraries for our models.
  • Close recursive loops so AI agents can drive their own training and infrastructure.
  • Work closely with the core research team on the systems they live inside.

Qualifications

  • High-performance, large-scale distributed systems experience, preferably for LLM workloads.
  • Proficiency in Python and PyTorch or JAX.
  • Hands-on experience with large-scale LLM training or inference technologies, e.g. SGLang, vLLM, verl, Megatron, OpenRLHF.
  • Good taste: you know when to build, when to buy, and when to delete.
  • AI-pilled: adopting agents, keen to build a company where agents are front and centre.

Skills

Required:Distributed systemsPythonPyTorch or JAXLLM training/inference techSystem design
Last updated Aug 20, 2026. Interested? Apply on the company site.
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About inherent

Recursively self-improving to discover new knowledge.

Recursively self-improving to discover new knowledge.

AIlabresearchinstitutioncollective intelligencerecursive self-improvementAI-driven scientific discovery
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