Senior AI Performance Engineer - Hybrid Cambridge

Pure Resourcing Solutions Limited; Dry Drayton; Hybrid; GBP 90,000 - 120,000; Full time

Benefits offered by this job

Competitive salary

Pension

Hybrid from Cambridge office

Exposure to AI/academic community

Job summary

Pure Resourcing Solutions Limited in Cambridge invites applications for Senior Performance Engineer, focusing on AI infrastructure. The role sits between research and engineering, turning live training and inference data into actionable models that evaluate optimizer ROI and hardware choices.

The successful candidate will design performance calculators, work with Python, CUDA, and DL tooling, and help shape purchasing and architecture across an ambitious AI ecosystem.

Qualifications

• A degree in computer science, mathematics, or something adjacent.
• A track record of building performance models or calculators (Python or spreadsheet-based) that forecast how a system will behave.
• Hands-on GPU/accelerator code optimisation, CUDA or similar.
• Genuine understanding of how LLMs and deep learning models run on hardware.
• Comfortable using Nsight or PyTorch Profiler and monitoring stacks.
• Python for data work with Pandas and NumPy.

Responsibilities

• Sit between research and engineering to extract live training/inference metrics.
• Build models and calculators to answer cost/benefit of optimisations.
• Assess ROI of accelerators and architecture changes.
• Influence purchasing and system design across the org and members.

Skills

Degree in CS/Math

Performance models/calculators

GPU/accelerator optimization

LLMs and DL hardware understanding

Profiling (Nsight)

Monitoring stacks (Prometheus Grafana)

Python data work (Pandas NumPy)

Postgraduate/research background

vLLM / inference serving

Open source contributions

Education

Degree in computer science or mathematics

Tools

Nsight

PyTorch Profiler

Prometheus

Grafana

Python

Pandas

NumPy

vLLM

CUDA

Job description

Pure Resourcing Solutions Limited in Cambridge invites applications for Senior Performance Engineer, focusing on AI infrastructure. The role sits between research and engineering, turning live training and inference data into actionable models that evaluate optimizer ROI and hardware choices.

The successful candidate will design performance calculators, work with Python, CUDA, and DL tooling, and help shape purchasing and architecture across an ambitious AI ecosystem.