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Fuse Energy is a forward-thinking renewable energy startup on a mission to deliver a terawatt of renewable energy – fast.

We're combining first-principles thinking with cutting-edge technology to build a radically better energy system. We raised $210M from top-tier investors including Multicoin, Balderton, Lakestar, Accel, Creandum, Lowercarbon, Ribbit, Box Group and strategic angels like Nico Rosberg, the Co-Founder of Solana and GPs behind Meta, Revolut, Spotify, Uber and more.

As data centres become one of the largest and fastest-growing sources of electricity demand, Fuse is expanding into high-performance compute infrastructure that sits at the intersection of energy and AI. We're building the GPU/CUDA performance layer and the inference serving layer at the same time, from scratch – and we're looking for the founding engineer to own the latter.

Responsibilities

  • Define Fuse's inference serving strategy and architecture from first principles.
  • Design and build the serving stack: request routing, batching, scheduling, and autoscaling for high-throughput, latency-sensitive inference workloads.
  • Own model-level optimisation strategy for serving – deciding where and how to apply quantisation, distillation, speculative decoding, and similar techniques to improve throughput and cost per token, partnering with the CUDA/GPU engineers.
  • Make the core software architecture calls on serving frameworks and orchestration (e.g. vLLM, TensorRT-LLM, SGLang, Triton Inference Server, or equivalents).
  • Translate throughput, latency, and uptime commitments into concrete technical specifications and serving capacity plans.
  • Act as a direct technical owner of inference performance and reliability.
  • Work closely with the CUDA and GPU engineering teams to ensure custom kernels and hardware performance work are integrated cleanly into the serving layer.
  • Set the standards, tooling, and benchmarks this function will run on as it grows.

Requirements

  • 4+ years of experience building or operating large-scale inference serving systems, or equivalent strong project/industry experience.
  • Deep, hands-on experience with inference serving frameworks and the techniques used to optimise them (batching, KV-cache management, quantisation, speculative decoding).
  • Strong systems thinking – able to reason about the full path from incoming request to served response across a large cluster.
  • Comfortable working directly with GPU/CUDA engineers to integrate low-level performance work into a serving system.
  • A track record of making high-stakes architecture calls and owning the outcome.
  • Comfort operating without a playbook – this is a founding role shaping a new function around architecture that's still early-stage, not joining an established one.

Benefits

  • Competitive salary and an equity sign-on bonus.
  • Biannual bonus scheme.
  • Fully expensed tech to match your needs.
  • Breakfast and dinner allowance for office-based employees.

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