Jobs in City of Edinburgh, United Kingdom (Now Hiring) — 1,663 open at 334 companies — Page 79

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 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, knowledge graphs, positioning and navigation, and cloud systems infrastructure. 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 and develops next-generation data management systems, with a focus on database kernels, query processing, storage engines, transaction processing, distributed data systems, and emerging AI Data infrastructure.

We are looking for researchers and engineers with strong systems backgrounds and a deep interest in building high-performance, scalable, and intelligent data management systems. The role is suitable for candidates with experience in one or more of the following areas: database systems, on-device AI, query optimization, query execution engines, storage and indexing, transaction processing, concurrency control, distributed databases, cloud-native data systems, hardware-aware database design, AI-native data management, and performance analysis.

The successful candidate will work on both exploratory research and practical system prototyping, contributing to technologies that may influence Huawei Cloud, GaussDB, and future data infrastructure for AI and intelligent applications.

Key Responsibilities:

Database Systems Research & Development

Design, implement, and evaluate core components of next-generation database and data management systems, including query optimisers, execution engines, storage engines, indexing structures, transaction processing, and distributed data processing frameworks.

Query Processing and Optimisation

Research and prototype advanced query planning and execution techniques for transactional, analytical, hybrid, and AI-driven workloads. Explore cost models, adaptive execution, vectorised execution, parallel execution, and workload-aware optimisation.

Storage, Indexing, and Data Layout

Develop efficient storage and indexing mechanisms for structured, semi-structured, multimodal, and AI-oriented data. Investigate data layout, caching, compression, memory hierarchy optimisation, and hardware-aware storage engine design.

Distributed and Cloud-Native Data Management

Explore distributed database architectures, data partitioning, replication, fault tolerance, distributed query execution, resource scheduling, and cloud-native data management techniques for large-scale deployment environments.

AI Data Infrastructure

Investigate database support for emerging AI workloads, including vector search, retrieval-augmented generation, agent memory, semantic data management, knowledge graph integration, multimodal data management, and AI-assisted query/data processing.

On-device AI

Develop techniques that can run on-device and can power the next generation of AI applications. Required skills: LLM quantization, on-device LLM inference, supervised and unsupervised LLM fine-tuning, parameter-efficient fine-tuning, knowledge distillation, gradient-free learning, memory for agentic AI.

Performance Optimization and Benchmarking

Conduct rigorous profiling, benchmarking, and empirical performance analysis of database kernels and data processing systems. Identify system bottlenecks and drive optimisation across CPU, memory, storage, network, and accelerator resources.

Research and Publications

Transform research ideas into high-quality prototypes, technical reports, patents, and publications at leading systems and database and AI venues such as SIGMOD, VLDB, ICDE, CIDR, EDBT, EuroSys, OSDI, SOSP, NSDI, and SoCC, NeurIPS, ICML, ICLR, AAAI.

Cross-Team Collaboration

Work closely with Huawei product teams, research teams, and academic collaborators. Communicate research findings, system designs, evaluation results, and technical trade-offs clearly to both 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:

• Master's, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, or a related discipline.

• Strong background in computer systems, database systems, AI systems, distributed systems, operating systems, or related areas.

• Solid understanding of database system principles, such as query processing, query optimization, storage engines, indexing, transaction processing, concurrency control, recovery, or distributed data management.

• Solid understanding of AI system principles, such as LLM quantization, on-device LLM inference, supervised and unsupervised LLM fine-tuning, parameter-efficient fine-tuning, knowledge distillation, gradient-free learning, memory for agentic AI.

• Hands-on experience in system design, implementation, evaluation, and performance debugging.

• Proficiency in one or more system-level programming languages, such as C, C++, Rust, or Go.

• Proficiency in one or more deep learning programmatic interfaces, e.g., Python, TensorFlow.

• Ability to conduct empirical systems research, including workload analysis, benchmarking, profiling, experiment design, and performance interpretation.

• Strong problem-solving skills and the ability to work on open-ended research and engineering problems.

• Effective technical communication skills and a collaborative mindset.

Desired:

• Experience contributing to database systems, data processing engines, storage systems, distributed systems, compilers, operating systems, or other low-level infrastructure projects.

• Knowledge of modern database architectures, such as distributed databases, HTAP systems, cloud-native databases, vector databases, graph databases, lakehouse systems, or AI-native data platforms.

• Experience with database internals in systems such as PostgreSQL, MySQL, DuckDB, Spark, Flink, Velox, ClickHouse, RocksDB, TiDB, CockroachDB, or similar systems.

• Familiarity with hardware-conscious system design, including multi-core CPUs, NUMA, RDMA, CXL, NVM, SSDs, GPUs, NPUs, or heterogeneous computing platforms.

• Experience with AI-related data infrastructure, such as vector search, embedding management, RAG systems, knowledge graphs, semantic data management, or agent-oriented memory systems.

• Publications in top-tier database, systems, or AI infrastructure venues are desirable but not essential.

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