Used Tools & Technologies
Machine Learning LLMRequired Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Kubernetes @ 2
Python @ 5
ETL @ 3
Deep Learning @ 3
AI @ 3
Reinforcement Learning @ 3
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The Science of Scaling team develops the next generation of large language models. In this role you will work at the intersection of research and engineering across the full stack — from low-level optimizations to high-level algorithm and experimental design — to build safe, steerable, and trustworthy AI systems.
Responsibilities
- Conduct research into the science of converting compute into intelligence
- Independently lead small research projects and collaborate on larger initiatives
- Design, run, and analyze scientific experiments to advance understanding of large language models
- Optimize training infrastructure to improve efficiency and reliability
- Develop developer tooling to enhance team productivity
Requirements
- Significant software engineering experience with a proven track record of building complex systems
- Proficiency in Python
- Experience with deep learning frameworks
- Hold at least a Bachelor's degree in a related field or equivalent experience (MS/PhD or strong research instincts encouraged)
- Results-oriented, flexible, and impact-focused mindset
- Comfortable with collaborative work (pair programming) and willing to take on tasks outside a narrow job description
- Interest in societal impacts of AI and AI safety
Preferred / Strong candidates may have
- Experience with JAX
- Experience with reinforcement learning
- Experience working on high-performance, large-scale ML systems
- Familiarity with accelerators, Kubernetes, and OS internals
- Experience with language modeling using transformer architectures
- Background in large-scale ETL processes
- Experience with distributed training at scale (thousands of accelerators)
Benefits / Compensation
- Annual salary range: £260,000 - £630,000 GBP
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours and a collaborative office environment
Logistics
- Location: London, United Kingdom
- Location-based hybrid policy: staff expected to be in one of Anthropic’s offices at least 25% of the time
- Education: at least a Bachelor's degree in a related field or equivalent experience required
- Visa sponsorship: Anthropic states they do sponsor visas and retain an immigration lawyer to assist (not guaranteed for every role/candidate)
How Anthropic works
Anthropic emphasizes working as a single cohesive team on a few large-scale research efforts, values empirical AI research, and hosts frequent research discussions. They encourage applicants from diverse backgrounds and provide guidance for candidate AI usage during the application process.