Data Infrastructure and AI Engineer

Huawei Technologies Research & Development (UK) Ltd; City of Edinburgh; Presencial; GBP 75 000 - 110 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

33 days annual leave entitlement

Group Personal Pension

Life insurance

Private medical insurance

Medical expense claim scheme

Employee Assistance Program

Cycle to work scheme

Company sports club and social events

Additional time off for learning and开发

Resumo da oferta

Huawei Edinburgh is seeking researchers/engineers to advance AI across data systems and intelligent applications. You will explore on-device learning, neurosymbolic reasoning, and foundational AI research, collaborating with academic partners and Huawei teams in the UK, Europe, and China.

The role emphasizes rigorous empirical research, prototyping, and translating findings into real-world AI-enabled data infrastructure and services, with opportunities to publish in leading venues.

Qualificações

• Master's or PhD in Computer Science, Mathematics, Statistics, or a related discipline.
• Strong foundations in AI/ML, probability, statistics and evaluation.
• Experience translating research into systems with benchmarking and experiments.

Responsabilidades

• Design and implement learning/inference methods for resource-constrained devices.
• Develop neurosymbolic learning methods combining symbolic and neural approaches.
• Publish high-quality research and transform ideas into prototypes and patents.
• Collaborate with Huawei teams and academic partners across locations.

Conhecimentos

C/C++

Python

Machine learning fundamentals

Formação académica

Master's or PhD in CS/Math/Stats

Ferramentas

PyTorch

TensorFlow

JAX

Descrição da oferta de emprego

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 organisation in the world with 96,000+ employees in research centres around the globe. In the UK, we already have design centres 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 Purpose

Working as part of the Huawei Database team will involve empirical computer science research, system design, and prototype implementation within the Huawei Edinburgh office. The role also includes close collaboration with local universities, academic researchers, and Huawei expert teams in the UK, Europe, and China.

The Edinburgh office brings together teams working on Database Systems, Programming Languages, Compilers, Retrieval and Agent Intelligence, Positioning and Navigation, and Systems and Distributed Scheduling. This creates a strong environment for multidisciplinary research at the intersection of data systems, AI, cloud computing, hardware acceleration, and software infrastructure.

This position offers an excellent opportunity to work on impactful research problems in modern data management, where research outcomes can be transferred into real-world database products, on-device AI-powered applications, and large-scale data platforms.

Job Summary

The Database team within the Huawei Edinburgh office develops next-generation data and AI systems, spanning database kernels, query processing, storage engines, transaction processing, distributed data systems, and emerging data infrastructure for intelligent applications.

We are looking for a researcher or engineer with rigorous foundations in artificial intelligence and machine learning, together with the ability to turn theory into working systems. The ideal candidate will have a strong command of learning, optimisation, probabilistic modelling, representation, and reasoning, and will apply these foundations across two closely connected areas: on-device AI and neurosymbolic learning.

The successful candidate will combine exploratory research with practical prototyping. They will develop learning and inference methods that operate under real device constraints and investigate principled ways to integrate neural and symbolic methods. The resulting technologies may influence Huawei Cloud, GaussDB, and future AI-enabled data infrastructure and intelligent applications.

Key Responsibilities:

On Device Learning and Inference

Design and implement efficient learning and inference methods for resource-constrained devices. Research may include model quantisation and compression, knowledge distillation, on-device LLM inference, parameter-efficient fine-tuning, supervised and unsupervised adaptation, gradient-free optimisation, continual or personalised learning, and memory for agentic AI. Evaluate accuracy, latency, memory use, energy efficiency, privacy, and robustness on representative hardware and workloads.

Neurosymbolic Learning and Reasoning

Develop principled methods that combine symbolic representations and reasoning—such as first-order logic, probabilistic logic programs, knowledge graphs, and learned rules—with neural architectures such as transformers. Work may cover statistical relational learning, rule mining, weak and incidental supervision, constrained learning, and convex and non-convex optimisation. Assess generalisation, uncertainty, interpretability, and robustness as well as predictive performance.

Foundational AI Research and Publications

Formulate clear research questions, connect proposed methods to relevant AI and machine learning foundations, and design rigorous experiments. Transform strong research ideas into high-quality prototypes, technical reports, patents, and publications for leading AI and machine learning venues such as NeurIPS, ICML, ICLR, AAAI, IJCAI, and KR.

Cross Team Collaboration

Work closely with Huawei product and research teams and with academic collaborators. Communicate research hypotheses, mathematical and algorithmic choices, system designs, evaluation results, and technical trade-offs clearly to research and engineering stakeholders.

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.

Person Specification:

Required:

• A Master's or PhD degree in Computer Science, Mathematics, Statistics, or a related discipline.
• A strong grounding in AI and machine learning fundamentals, including probability and statistics, optimisation, neural networks and representation learning, and the principles of sound model evaluation.
• Demonstrated depth in at least one of the role's core areas—on-device learning and inference or neurosymbolic learning and reasoning—and the ability and motivation to work across both.
• Hands-on experience translating research ideas into implemented and evaluated systems, including performance analysis and debugging.
• Proficiency in one or more systems programming languages, such as C, C++, or Rust.
• Proficiency in Python and practical experience with at least one modern machine learning framework, such as PyTorch, JAX, or TensorFlow.
• Ability to conduct rigorous empirical research, including benchmark and workload design, profiling, ablation studies, baselines, reproducible experimentation, and careful interpretation of results.
• Strong problem-solving skills and the ability to make progress on open-ended research and engineering problems.
• Effective technical communication skills and a collaborative approach to multidisciplinary research.
• Evidence of research excellence in AI or machine learning, demonstrated through high-quality publications or equivalent research contributions.

What We Offer

• 33 days annual leave entitlement per year (including UK public holidays)
• Group Personal Pension
• Life insurance
• Private medical insurance
• Medical expense claim scheme
• Employee Assistance Program
• Cycle to work scheme
• Company sports club and social events
• Additional time off for learning and development