Research Engineer, Science of Scaling

Benefits

Parental leave

Not verified

Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

GBP 260K-630K From the posting source checked Jun 20, 2026

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

U.S. benchmark only; posted salary is not compared across countries or currencies.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Research Engineer, Science of Scaling London, UK About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic is seeking a Research Engineer/Scientist to join the Science of Scaling team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems. You'll contribute across the entire stack, from low-level optimizations to high-level algorithm and experimental design, balancing research goals with practical engineering constraints. Responsibilities: - Conduct research intro the science of converting compute into intelligence - Independently lead small research projects while collaborating with team members on larger initiatives - Design, run, and analyze scientific experiments to advance our understanding of large language models - Optimize training infrastructure to improve efficiency and reliability - Develop dev tooling to enhance team productivity You may be a good fit if you: - Have significant software engineering experience and a proven track record of building complex systems - Hold an advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field - Are proficient in Python and experienced with deep learning frameworks - Are results-oriented with a bias towards

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