LLM Research Engineer – Foundational AI & Data Pipelines

Thomson Reuters; Greater London; Hybrid; GBP 150,000 - 200,000; Full time

Job summary

A global information provider is seeking a Machine Learning Research Engineer to join their innovative team. This role involves designing robust systems for training and evaluating large language models as well as collaborating with world-class researchers. Successful candidates will hold a relevant degree and have extensive experience in ML, AI, and software engineering practices. The position is based in Greater London and offers a competitive compensation package and hybrid work model.

Benefits

Competitive compensation and benefits

Flexible working environment

Learning and development opportunities

Social impact initiatives

Qualifications

• 3 years of hands-on experience building ML/NLP/AI systems.
• Demonstrated expertise in building production-quality code.
• Proficiency in modern AI development frameworks.
• Understanding of LLM training methodologies.

Responsibilities

• Design and implement robust scalable systems for training LLMs.
• Rapidly implement novel research ideas in LLM training.
• Build pipelines for synthetic data generation and automation.
• Collaborate with researchers to translate research into practice.
• Engage in sharing technical implementations and best practices.

Skills

Machine Learning

Python

AI

Natural Language Processing

Robotics

Education

Bachelor's or Master's degree in Computer Science or relevant discipline

Tools

PyTorch

TensorFlow

Jax

HuggingFace Transformers

Job description

A global information provider is seeking a Machine Learning Research Engineer to join their innovative team. This role involves designing robust systems for training and evaluating large language models as well as collaborating with world-class researchers. Successful candidates will hold a relevant degree and have extensive experience in ML, AI, and software engineering practices. The position is based in Greater London and offers a competitive compensation package and hybrid work model.