Graduate Performance Engineer

Huawei UK Research Center; United Kingdom; On-site; GBP 30,000 - 45,000; Full time

Job summary

A leading research organization in the UK is seeking a Graduate Performance Engineer to join their workload modeling team. The ideal candidate will work on performance projection and architectural studies focused on server CPUs and AI workloads. You will develop performance models and enhance simulation features. A strong understanding of CPU architecture, proficiency in C/C++, and experience with performance analysis tools are essential for this role. The position offers competitive salary and potential for career growth.

Qualifications

• Strong understanding of CPU architecture.
• Proficient in performance analysis methodologies.
• Experience in C/C++ and Python.

Responsibilities

• Develop and enhance simulation features for workload modeling.
• Conduct in-depth performance projections for various workloads.
• Collaborate with cross-functional teams for data analysis.

Skills

Strong understanding of CPU architecture and micro-architecture performance techniques

Proficient in performance analysis and workload characterization

Experience in developing using dynamic binary instrumentation infrastructures

Proficiency in C/C++

Experience with Python and other scripting languages

Excellent analytical and problem-solving skills

Education

Bachelor's degree in Computer Science or related field

Tools

QEMU

DynamoRIO

GEM5

Linux perf

Job description

Organisation/Company Huawei UK Research Center Research Field Computer science » Computer architecture Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Established Researcher (R3) Country United Kingdom Application Deadline 31 Aug 2025 - 00:00 (UTC) Type of Contract To be defined Job Status Negotiable Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

Graduate Performance Engineer (Workload Modelling and Simulation)


About Huawei

With a bold vision of bringing digital to every person, home, and organization for a fully connected, intelligent world, Huawei stands as a global leader in ICT solutions. Our workforce of 194,000 spans over 170 countries, crafting unparalleled experiences in telecom networks, IT, smart devices, and cloud services.

About Huawei UK (R&D)

Huawei has the largest Research and Development organization in the world with 96,000+ employees in research centers around the globe. In the UK, we already have design centers in Cambridge, London, Edinburgh and Ipswich. We continue to explore and define new research directions and new services. We have expanded our collaborations with academic researchers; researched new network architectures, integration of communications and key enabling technologies; and developed the fundamental theories of these technologies. We invite you to join us on this exciting journey and drive your career forward.

Job Summary

We are seeking a highly motivated and enthusiastic Graduate Performance Engineer to join our dynamic workload modelling team. In this role, you will have the opportunity to work on cutting-edge projects involving performance projection, simulation, and architectural studies, with a focus on server CPUs, NPUs, and AI workloads. As a Graduate Performance Engineer, you will contribute to the development of performance models for upcoming server processors and accelerators, support architectural studies, and drive software/hardware co-optimization for next-generation systems.

Key Responsibilities:

Develop and enhance simulation features to enable rapid architectural exploration and performance evaluation of server CPUs and NPUs, focusing on AI and large-scale data analytics workloads.

Conduct in-depth performance projections for various workloads, including databases, distributed storage, and engines for AI and data analytics.

Contribute to architectural studies to explore and evaluate the latest server CPU core and SOC designs.

Work on characterizing workloads and developing methodologies for tracing and optimizing AI models to enhance simulation and performance analysis.

Construct a non-intrusive, highly accurate system for characterizing and modelling complex workloads, ensuring precise workload representation.

Collaborate with cross-functional teams to extract and analyze real-world workload features, contributing vital data for hardware development.

Ideal Candidate:

Strong understanding of CPU architecture and micro-architecture performance techniques (e.g., branch prediction, prefetchers, cache hierarchies).

Proficient in performance analysis and workload characterization, with hands-on experience in methodologies for system-level architectural exploration.

Experience in developing using dynamic binary instrumentation infrastructures like QEMU or DynamoRIO or x86 PIN.

Proficiency in C/C++, with a solid understanding of Assembly Language.

Experience with Python and other scripting languages to support automation, data processing, and tool development.

Excellent analytical and problem-solving skills with the ability to work both independently and as part of a team.

Considered as a plus

Experience in compiler technologies, binary analysis, and performance tuning.

Experience in developing and using performance simulators like GEM5 (O3 model), Sniper or others

Knowledge of AI workloads and the challenges involved in optimizing large-scale models for performance simulation.

Experience in Linux kernel development, including knowledge of kernel internals.

Hands-on experience in CPU performance analysis, utilizing methodologies such as PMU-based profiling and TopDown Analysis, and proficiency with performance analysis tools like Linux perf.