At a Glance
- Tasks: Work with senior engineers to create predictive models for AI performance.
- Company: Dynamic Cambridge-based organisation at the forefront of AI research.
- Benefits: Hybrid work, pension scheme, and exposure to the AI academic scene.
- Other info: Collaborative team culture with opportunities for growth and learning.
- Why this job: Gain hands-on experience and mentorship in a cutting-edge AI environment.
- Qualifications: Postgraduate research background with strong Python and performance modelling skills.
The predicted salary is between 63000 - 77000 £ per year.
Overview
In this junior role you will work with senior engineers to convert live training and inference metrics into predictive models and decision tools.
You’ll help determine whether alternative hardware setups and configurations are worth shipping, contributing to cost-aware, performance-driven AI infrastructure.
The position offers hands-on ownership early and close mentorship, within a Cambridge-based, research-connected organization.
- Pay / Benefits
- Pension
- hybrid from Cambridge office
- exposure to wider AI and academic scene
Responsibilities
- Collect real metrics from live training and inference jobs
- Build performance models and calculators to answer questions about deployment viability and cost
- Collaborate with senior engineers and receive close guidance
- Own small-to-medium scope modeling tasks and iterate towards tangible predictions
- Key requirements
- Postgraduate research background; Ph D preferred, master's considered
- Strong grasp of computer architecture fundamentals and how LLMs and DL models run on hardware
- Experience building performance models or forecasting tools (Python or spreadsheets)
- Hands-on CUDA or similar GPU/accelerator code experience
- Familiarity with profiling tools (Nsight, Py Torch Profiler) and monitoring stacks (Prometheus, Grafana)
- Strong Python for data work; Pandas and Num Py
- Exposure to inference serving frameworks like v LLM is a plus
- strong problem-solving abilities
- quick learner
- collaborative and proactive communication
- CUDA
- Nsight
- Py Torch Profiler
Performance Engineer (Junior) | AI Infrastructure | Cambridge (Hybrid) | employer: Pure Resourcing Solutions
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