Lead Inference Engineer

Plexus has partnered with a rapidly growing AI company looking for a GPU Performance Engineering Lead to build and lead a specialist infrastructure team.

This is a hands-on leadership role focused on improving the speed, efficiency and reliability of large-scale AI workloads. You’ll set the technical direction, hire the team and work directly on complex performance challenges across distributed GPU infrastructure.

Responsibilities:

• Own the technical strategy for LLM inference performance

• Recruit and lead the Inference Optimisation team

• Optimise latency, throughput and cost per token across GPU infrastructure

• Benchmark inference engines, quantisation methods and parallelism strategies

• Improve inference routing and load balancing

• Evaluate new kernels, hardware and optimisation techniques

Requirements:

• 8+ years in performance optimisation, HPC or GPU engineering

• 5+ years leading engineering teams

• Production experience with vLLM, SGLang or similar inference engines at scale

• Strong knowledge of GPU architecture, distributed inference and quantisation

• Experience with GPU profiling tools such as Nsight or PyTorch Profiler

• Proficiency in Python, Rust or Go

• C++, CUDA or Triton experience is highly desirable

Offer:

• $270k–$330k base salary

• Fully remote within the US

• Opportunity to build and lead the inference function

• Work on high-volume AI infrastructure and cutting-edge GPU technology

If this piques your interest, please apply now!