Junior AI Performance Engineer – Hybrid (Cambridge)

Pure Resourcing Solutions Limited; Cambridgeshire and Peterborough; Hybrid; GBP 42,000 - 70,000; Full time

Benefits offered by this job

Pension

Hybrid from Cambridge office

Job summary

Pure Resourcing Solutions Limited is recruiting a Performance Engineer (Junior) for Cambridge (Hybrid) up to 70k. You will work with senior engineers to build models predicting hardware performance from live training/inference metrics and turn data into actionable forecasts.

The role suits a strong academic with hands-on modeling, profiling, and Python data skills. The position offers hybrid work from Cambridge, exposure to AI infrastructure challenges, and the chance to influence decisions

Qualifications

• Postgraduate research background; PhD strongly preferred, exceptional master's graduates considered
• Solid grasp of computer architecture fundamentals and how LLMs run on hardware
• Experience building performance models or forecasting tools from research or projects
• Hands-on GPU/accelerator code experience (CUDA or equivalent)
• Familiarity with profiling and monitoring stacks (Nsight, PyTorch Profiler; Prometheus, Grafana)
• Strong Python for data work; Pandas and NumPy

Responsibilities

• Build and validate performance models from live training/inference metrics
• Turn metrics into calculators to answer whether to ship a change and cost implications
• Work with senior engineers for ownership and rapid iteration
• Contribute to monitoring and profiling workflows to improve hardware efficiency

Skills

PhD in CS

Computer architecture

LLMs on hardware

Performance modeling

Python data work

GPU/CUDA

Profiling tools

Monitoring stacks

Pandas & NumPy

Education

PhD in CS/Math/Physics

Tools

Nsight

PyTorch Profiler

Prometheus

Grafana

Job description

Pure Resourcing Solutions Limited is recruiting a Performance Engineer (Junior) for Cambridge (Hybrid) up to 70k. You will work with senior engineers to build models predicting hardware performance from live training/inference metrics and turn data into actionable forecasts.

The role suits a strong academic with hands-on modeling, profiling, and Python data skills. The position offers hybrid work from Cambridge, exposure to AI infrastructure challenges, and the chance to influence decisions