System Performance Engineer

AI Systems Performance Engineer

Location: UK / Hybrid

We are partnering with an innovative technology company developing advanced solutions to improve the performance and efficiency of modern AI systems.

The team works on challenging engineering problems across artificial intelligence, software optimisation, and computing platforms. Their work focuses on understanding how complex AI workloads execute and developing new approaches to improve speed, efficiency, and scalability.

This is an opportunity to join a highly technical R&D environment where you will work across the AI stack, combining software engineering, performance analysis, and systems-level optimisation to solve complex problems.

The Role

As an AI Systems Performance Engineer, you will work on improving the efficiency and execution of demanding AI workloads across modern computing environments.

You will be responsible for:

• Developing and optimising software components that improve AI workload performance
• Analysing AI models and applications to identify performance bottlenecks
• Improving execution efficiency across AI frameworks, runtimes, and computing platforms
• Working across different layers of the AI stack, from models and algorithms through to underlying systems
• Building prototypes, benchmarks, and tools to evaluate performance improvements
• Applying techniques from performance engineering, software optimisation, and systems analysis
• Investigating new approaches to make AI applications faster, more efficient, and more scalable
• Collaborating with engineers working across software, systems, and hardware domains

What We’re Looking For

We are looking for an engineer with strong experience in AI systems, software optimisation, and performance-focused engineering.

You will ideally have:

• MSc or PhD in Computer Science, Computer Engineering, Mathematics, Physics, or a related technical discipline
• Experience optimising compute-intensive workloads, particularly within AI or machine learning environments
• Strong understanding of computer architecture and modern computing systems
• Experience with performance analysis tools such as profilers, debuggers, benchmarking tools, or similar
• Strong programming skills in C++, Python, or comparable languages
• Experience investigating complex technical challenges and developing practical solutions
• Ability to communicate technical concepts clearly and work effectively within a collaborative engineering team

Desirable Experience

Experience in any of the following areas would be beneficial:

• AI inference optimisation
• Machine learning frameworks and runtimes
• GPU or accelerated computing environments
• Compiler optimisation
• Kernel development
• High-performance computing
• Parallel computing
• Hardware/software interaction
• Large-scale AI applications