Why This Role Stands Out
This role offers a unique opportunity to contribute to cutting-edge ML systems and compilers at a globally recognized technology leader, providing significant career growth within a dynamic R&D environment. You'll thrive here if you're a mid-senior level engineer passionate about innovation and eager to push the boundaries of AI technology. Apply now to join a team dedicated to shaping the future of intelligent systems.
Quick Overview
Job Description
About Huawei Research and Development UK Limited
Founded in 1987, Huawei is a leading global provider of information and communications technology (ICT) infrastructure and smart devices. We have 207,000 employees and operate in over 170 countries and regions, serving more than three billion people around the world.
Our vision and mission is to bring digital to every person, home and organization for a fully connected, intelligent world. To this end, we will drive ubiquitous connectivity and promote equal access to networks; bring cloud and artificial intelligence to all four corners of the earth to provide superior computing power where you need it, when you need it; build digital platforms to help all industries and organizations become more agile, efficient, and dynamic; redefine user experience with AI, making it more personalized for people in all aspects of their life, whether they’re at home, in the office, or on the go.
This spirit of innovation has led Huawei to work in close partnership with leading academic institutions in the UK to develop and refine the latest technologies. With a shared commitment to innovation and progress, both parties have worked together to achieve common goals and establish a strong partnership. The partnership between UK and Huawei help to develop the technologies of the future that will transform the way we all communicate, work and live.
For the past 30 years we have maintained an unwavering focus, rejecting shortcuts and easy opportunities that don't align with our core business. With a practical approach to everything we do, we concentrate our efforts and invest patiently to drive technological breakthroughs.
This strategic focus is a reflection of our core values:
Staying customer-centric,
Inspiring dedication,
Persevering,
Growing by reflection.
Huawei Research and Development UK Limited Overview
Huawei’s vision is a fully connected, intelligent world. To achieve this, we work to inspire passion for basic research around the world. Our combined passion drives development across the global innovation value chain. 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 a CPU research team working where AI meets low-level systems. We use LLMs, agents and reinforcement learning to optimise CPUs, operating system kernels, compilers and language runtimes on ARM64 platforms.
We are looking for an engineer who is comfortable writing a compiler pass, a JIT or interpreter fast path, and a training loop. Ideally you have built at least one of those from scratch because you wanted to understand how it works.
Key Responsibilities:
• Design and train RL and LLM-based agents that discover and verify performance optimisations in kernels, language runtimes and compiler output.
• Build the infrastructure around those agents: reward design, sandboxed execution environments, benchmark harnesses, and verification that catches reward hacking.
• Write and optimise performance-critical code, such as compiler passes, interpreter and JIT hot paths, and runtime data structures, and measure it rigorously on real hardware.
• Turn research papers into working prototypes quickly, and turn strong prototypes into patents and publications.
• Work with CPU architects and kernel and compiler engineers to turn ML-driven insights into hardware-software co-design proposals.
This job description is only an outline of the tasks, responsibilities and outcomes required of the role. The jobholder will carry out any other duties as may be reasonably required by his/her line manager. The job description and personal specification may be reviewed on an ongoing basis in accordance with the changing needs of Huawei Research and Development UK Limited.
Required:
• BSc or MSc in Computer Science, Electrical Engineering or a related field, or equivalent practical experience.
• Strong C++ and Python.
• Hands-on experience in at least two of the following areas:
– compiler infrastructure (LLVM, MLIR, or a custom compiler)
– language runtimes (JIT compilers, interpreters, or dynamic language VMs such as V8, JavaScriptCore, PyPy, LuaJIT or the JVM)
– training or post-training models, including reinforcement learning (PPO, GRPO, or RLHF-style)
• Evidence of building a non-trivial system end-to-end. Examples include an open-source project, a language, a compiler, a runtime, or a tool you designed yourself.
Desired:
• CPU microarchitecture knowledge: pipelines, branch prediction, caches and prefetching, and how software behaviour maps onto them.
• ARM64/AArch64 and NEON/SVE/SME; simulation with gem5 or QEMU.
• Dynamic language runtime internals: inline caches, hidden classes/shapes, tiered compilation, deoptimisation, garbage collection.
• MLIR dialects and custom lowering passes, or LLVM backend work (instruction selection, register allocation).
• Low-level kernel work in CUDA, Triton or SIMD intrinsics.
• Quantisation and efficient inference (INT4/FP8, GPTQ/AWQ, KV-cache management).
• RL environment design for multi-step, tool-using agents.
• Distributed training (DeepSpeed, Ray, NCCL).
• Publications, patents, or widely used open-source work.
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