[Hiring] AI Inference Engineer @Fuse Energy

Role Description

Fuse Energy is expanding into high-performance compute infrastructure at the intersection of energy and AI. We're looking for the founding engineer to own the inference serving layer, reporting directly to the CTO. You'll be responsible for:

• Defining Fuse's inference serving strategy and architecture from first principles
• Designing and building the serving stack: request routing, batching, scheduling, and autoscaling for high-throughput, latency-sensitive inference workloads
• Owning 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
• Making core software architecture calls on serving frameworks and orchestration (e.g. vLLM, TensorRT-LLM, SGLang, Triton Inference Server or equivalents)
• Translating throughput, latency, and uptime commitments into concrete technical specifications and serving capacity plans
• Acting as direct technical owner of inference performance and reliability
• Working closely with the CUDA and GPU engineering teams to integrate custom kernels and hardware performance work cleanly into the serving layer
• Setting the standards, tooling, and benchmarks this function will run on as it grows

Qualifications

• 4+ years 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, not joining an established one

Requirements

• Bonus: Triton or custom ML inference/training frameworks; autoscaling or capacity planning for large-scale inference; multi-tenant serving or SLA-driven infrastructure; background at a hyperscaler, frontier AI lab or large-scale distributed inference system; Kubernetes/Slurm; interest in energy markets, grid systems or sustainability-focused compute

Benefits

• Competitive salary and eligibility for equity
• Biannual bonus scheme
• Fully expensed tech to match your needs
• Private health insurance
• Breakfast and dinner allowance for office-based employees
• As we hire globally, benefits vary by location.