Fuse Energy

Fuse Energy is a leading UK electricity supplier prioritizing affordability, service excellence, and sustainability through renewable energy projects and global reinvestment efforts.

Renewable Electricity

Utilities

11-50 (30)

Founded 2014

$78M raised

14 open positions

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AI Inference Engineer

2 weeks, 3 days ago

United Kingdom

Full-time

Senior

AI Engineer

DevOps and Infrastructure

Kubernetes

Apply Now

Fuse Energy

Fuse Energy is a leading UK electricity supplier prioritizing affordability, service excellence, and sustainability through renewable energy projects and global reinvestment efforts.

Renewable Electricity

11-50

Founded 2014

$78M raised

View All Jobs 14

Description

Define Fuse's inference serving strategy and architecture from first principles.
Design and build the serving stack for request routing, batching, scheduling, and autoscaling.
Own model-level optimization for serving, including quantization, distillation, and speculative decoding.
Select and evaluate serving frameworks and orchestration tools such as vLLM, TensorRT-LLM, SGLang, and Triton Inference Server.
Translate throughput, latency, and uptime commitments into technical specifications and capacity plans.
Own inference performance and reliability for the serving layer.
Collaborate with CUDA and GPU engineering teams to integrate low-level performance improvements.
Set standards, tooling, and benchmarks for the function as it scales.

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 optimization techniques such as batching, KV-cache management, quantization, and speculative decoding.
Strong systems thinking across the full request-to-response path in a large cluster.
Comfort working directly with GPU/CUDA engineers to integrate low-level performance work.
Track record of making high-stakes architecture decisions and owning the outcome.
Ability to operate without a playbook in a founding, early-stage role.
Experience with Triton or custom ML inference/training frameworks (preferred).
Experience with autoscaling or capacity planning for large-scale inference workloads (preferred).
Exposure to multi-tenant serving or SLA-driven infrastructure (preferred).
Background at a hyperscaler, frontier AI lab, or large-scale distributed inference system (preferred).
Familiarity with Kubernetes or Slurm for cluster orchestration (preferred).
Interest or experience in energy markets, grid systems, or sustainability-focused compute (preferred).

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.

Interested in this position?

Apply directly on the company website

Apply Now

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