Junior AI Performance Engineer - Hybrid Cambridge

Pure Resourcing Solutions; Cambridge; Hybrid; GBP 63,000 - 77,000; Full time

Job summary

Pure Resourcing Solutions is seeking a Junior Performance Engineer for AI infrastructure based in Cambridge with a hybrid work model. You will work with senior engineers to extract live metrics from training/inference workloads and build predictive models to decide if optimisations are worth shipping.

The role targets academically exceptional candidates (ideally PhD), who can dive into hardware-aware AI performance challenges and deliver practical forecasting tools in Python.

Qualifications

• Postgraduate research background, PhD preferred
• Strong grasp of computer architecture and how LLMs and deep learning models run on hardware
• Experience building performance models or forecasting tools in Python or spreadsheet-based
• Hands-on work with GPU or accelerator code (CUDA or similar)
• Familiarity with profiling tools (Nsight, PyTorch Profiler) and monitoring stacks (Prometheus, Grafana)
• Strong Python for data work, Pandas and NumPy

Responsibilities

• Pull real metrics from live training and inference jobs and turn them into models and calculators
• Assess whether a given optimisation is worth shipping
• Own performance models with senior support nearby

Job description

Pure Resourcing Solutions is seeking a Junior Performance Engineer for AI infrastructure based in Cambridge with a hybrid work model. You will work with senior engineers to extract live metrics from training/inference workloads and build predictive models to decide if optimisations are worth shipping.

The role targets academically exceptional candidates (ideally PhD), who can dive into hardware-aware AI performance challenges and deliver practical forecasting tools in Python.