Senior Performance Engineer

CommonAI CIC; Cambridge; On-site; GBP 70,000 - 100,000; Full time

Benefits offered by this job

Competitive salary

Pension

Professional development

Office near Cambridge train station

Collaborative environment

Job summary

CommonAI CIC in Cambridge is seeking a Senior Performance Engineer to collaborate with AI researchers and software engineers. You will instrument and collect granular metrics from inference and training jobs to build predictive models of software optimisations and hardware changes.

Your work will influence hardware purchasing decisions and architectural optimisations to keep AI workloads fast and cost-effective.

Qualifications

• Degree in computer science, mathematics or adjacent field.
• Experience building mathematical models and performance calculators.
• Experience optimizing GPU code (CUDA).
• Understanding of DL hardware, inference vs training.
• Proficiency with profiling and monitoring tools: Nsight, PyTorch Profiler, Prometheus, Grafana.
• Python for data analysis (Pandas, NumPy).

Responsibilities

• Instrument and collect granular metrics from inference and training jobs.
• Develop mathematical models to predict performance under changes.
• Influence hardware purchasing decisions and architectural optimisations.
• Ensure AI workloads run efficiently and cost-effectively.

Skills

Mathematical modeling

Education

Degree in Computer Science/Mathematics or adjacent field

Tools

NVIDIA Nsight

PyTorch Profiler

Prometheus

Grafana

Pandas

NumPy

CUDA

Job description

CommonAI CIC is a non-profit membership organisation, founded on a belief in collaborative engineering for the safe and responsible development of foundational AI technologies. A place where AI startups, enterprises large and small, public sector bodies and academia can share resources and knowledge, to codevelop and grow businesses, fast.

We are seeking a Senior Performance Engineer to join our rapidly growing team. In this role, you will work with AI researchers and software engineers to build up a detailed understanding of how their applications are performing. You will instrument and collect granular metrics from inference and training jobs and use that information to develop sophisticated mathematical models that predict how software optimisations and architectural or hardware changes will impact system performance.

Your work will directly influence both our in-house and member's hardware purchasing decisions and architectural optimisations, ensuring teams can run AI workloads efficiently and cost-effectively.

Requirements

This role requires a degree in computer science, mathematics or an adjacent field. You should also be able to demonstrate:

• Significant experience building insightful mathematical models and performance calculators (Excel/Google Sheets or Python modelling experience) to forecast system behaviour
• Optimisation of code running on GPUs and/or other accelerators (e.g. CUDA)
• Solid understanding of computer architecture fundamentals and how LLMs and Deep Learning models execute on that hardware (inference vs. training, matrix multiplication, KV-caching, etc.)
• Proficiency with profiling tools (NVIDIA Nsight, PyTorch Profiler) and monitoring stacks (Prometheus, Grafana)
• Capability to work in Python for data analysis (Pandas, NumPy) and scripting

The following are also highly valued:

• Post-graduate degrees and research experience in relevant fields (please list your publications).
• Deep understanding of inference serving frameworks (e.g. vLLM)
• Background in statistical analysis
• Contributions to open source and/or research projects

Benefits

• A collaborative and supportive work environment
• The opportunity to have a high impact in a growing organisation
• Competitive salary package and pension
• Professional development opportunities
• Networking opportunities with influential people from across the tech sector and academia
• A vibrant office environment located a few minutes' walk away from Cambridge train station