Machine Learning Scientist – RL & AI Systems

Huawei Technologies Research & Development (UK) Ltd; Greater London; On-site; GBP 80,000 - 120,000; Full time

Job summary

Huawei Research and Development UK Limited seeks a highly skilled Machine Learning Scientist/Engineer in London. You will advance RL, BO, AI agents, LLMs, and VLMs, balancing core research with applied development.

The role blends theoretical innovation with building scalable systems and collaborating with diverse teams. You will work in a fast-paced environment, focusing on cutting-edge reinforcement learning and language-model tuning to solve real-world challenges.

Qualifications

• Master’s or PhD in Computer Science, ML, AI, or related field.
• Expertise in AI/ML topics, RL or LLM tuning, demonstrated by publications or code.
• Strong Python proficiency and hands-on PyTorch experience.
• Ability to adapt quickly and deliver impact in new projects.
• Experience thriving in a fast-paced, research-driven environment.

Responsibilities

• Research & Development: design, implement, and evaluate novel RL/AI algorithms and architectures.
• System Implementation: translate research into prototypes and scalable systems.
• Publications & Open Source: contribute original work to conferences or open-source.
• Cross-functional Collaboration: partner with multidisciplinary teams to deploy research.
• Adaptability & Innovation: solve problems across domains as business needs evolve.

Skills

Python

PyTorch

Reinforcement Learning

LLM tuning

Research mindset

Education

Master’s or PhD in CS/ML/AI

Tools

TRL

Distributed multi-GPU training

Job description

Huawei Research and Development UK Limited seeks a highly skilled Machine Learning Scientist/Engineer in London. You will advance RL, BO, AI agents, LLMs, and VLMs, balancing core research with applied development.

The role blends theoretical innovation with building scalable systems and collaborating with diverse teams. You will work in a fast-paced environment, focusing on cutting-edge reinforcement learning and language-model tuning to solve real-world challenges.