Research Scientist - Machine Learning (Contractor)

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

The Reinforcement Learning Team at the Huawei London Research Centre is seeking a highly skilled and research-driven Machine Learning Scientist to join our team. Our group combines world-class research with impactful applications, earning top honors such as NeurIPS 2020 Black Box Optimisation Challenge – Winners

, multiple Best Paper and Best Systems Paper Awards, and industry recognition, including Huawei’s Gold Medals and Best Technology Breakthroughs.

This role focuses on advancing the state-of-the-art in reinforcement learning, Bayesian optimisation, AI agents, large language models (LLMs), and/or vision-language models (VLMs). You will work at the intersection of fundamental research and applied innovation, developing novel algorithms, architectures, and systems that push the boundaries of AI capabilities.

This is a unique opportunity to contribute to high-impact AI research while collaborating with a multidisciplinary and multinational team of scientists and engineers. We value scientific excellence, demonstrated by a strong publication record at top-tier venues, and an eagerness to translate cutting-edge ideas into working prototypes and real-world applications.

Key Responsibilities:

• Conduct original research in RL, BO, AI agents, LLMs, and VLMs, leading to publications in top conferences and journals (e.g., NeurIPS, ICLR, ICML, JMLR, and others).