Machine Learning Scientist

Thomson Reuters; City of Westminster; Hybrid; GBP 80,000 - 100,000; Full time

Job summary

A leading news and information company in the UK is seeking a Machine Learning Research Engineer to design and implement machine learning systems with a focus on real-world applications. Responsibilities include developing evaluation metrics, prototyping generative models, and integrating feedback for model improvements. Candidates should have experience in computational biology or ML applications in life sciences and training in natural sciences. Competitive compensation and flexible working arrangements are offered.

Benefits

Competitive compensation and benefits

Comprehensive health coverage

Retirement contributions

Generous leave policies

Flexible working arrangements

Opportunities for travel and development

Qualifications

• Experience in computational biology, protein design, or ML applications in life sciences.
• Academic training or exposure to natural sciences (physics, biology, chemistry).

Responsibilities

• Develop machine learning systems for real-world impact.
• Define evaluation metrics aligned with practical objectives.
• Rapidly prototype generative modeling approaches.

Skills

Experience in computational biology

Machine learning applications

Natural sciences knowledge

Job description

Machine Learning Research Engineer (Foundational Research)

Overview

Join a cutting‑edge research team at Thomson Reuters to design, build, and experiment with large language models (LLMs) in an academic environment.

Responsibilities

• Develop machine learning systems with real‑world impact (~90%): help curate training and evaluation datasets.
• Define and implement evaluation metrics aligned with practical objectives.
• Rapidly prototype and iterate on generative modeling approaches.
• Collaborate in a shared codebase with colleagues across research and engineering.
• Support the infrastructure used for compute, experimentation, and model development.
• Work with experimental teams to plan laboratory testing and run model inference for biological targets.
• Integrate laboratory feedback data into model improvements.
• Stay informed about the latest advances in machine learning.
• Develop working knowledge of protein science and cellular biology.
• Participate in internal knowledge‑sharing activities.
• Attend relevant scientific or technical events.

Qualifications

• Experience in computational biology, protein design, or ML applications in the life sciences.
• Academic training or professional exposure to natural sciences such as physics, biology, or chemistry.

Benefits

• Competitive compensation and benefits.
• Comprehensive health coverage.
• Retirement contributions.
• Generous leave policies, including inclusive parental leave.
• Flexible and hybrid working arrangements.
• Opportunities for travel and professional development.

We encourage applicants from all backgrounds and are committed to fostering a diverse and inclusive team.