LLM Research Engineer: Data-Driven AI & Evaluation

Thomson Reuters; Slough; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A global information and technology company is seeking a Machine Learning Research Engineer to join their innovative research team. The chosen candidate will focus on training and evaluating large AI models while collaborating closely with academic experts and internal teams. This role involves implementing scalable systems and pushing the boundaries of AI research through hands-on experience and technical proficiency. In a flexible hybrid work environment, you'll also contribute to industry-leading advancements with a strong emphasis on data and collaboration.

Benefits

Flexible hybrid work model

Career development opportunities

Comprehensive benefit plans

Two paid volunteer days annually

Mental Health Days off

Qualifications

• Experience with ML libraries or frameworks, especially in training or evaluation.
• Hands-on experience with data-centric ML approaches.
• Strong interest in ML research literature.

Responsibilities

• Design and implement systems for training and evaluating large language models.
• Collaborate with researchers to translate research into practical implementations.
• Engage in documenting and sharing best practices within the team.

Skills

Machine Learning impact

LLM training techniques

Data pipelines

ML training infrastructure

Collaborative skills

Education

Bachelor's or Master's degree in relevant field

Tools

AWS

Google Cloud

Azure

Job description

A global information and technology company is seeking a Machine Learning Research Engineer to join their innovative research team. The chosen candidate will focus on training and evaluating large AI models while collaborating closely with academic experts and internal teams. This role involves implementing scalable systems and pushing the boundaries of AI research through hands-on experience and technical proficiency. In a flexible hybrid work environment, you'll also contribute to industry-leading advancements with a strong emphasis on data and collaboration.