Research Engineer, Science of Scaling

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 flexibility and impact Enjoy pair programming and collaborative work, and are willing to take on tasks outside your job description to support the team View research and engineering as two sides of the same coin, seeking to understand all aspects of the research program to maximize impact Care about the societal impacts of your work and have ambitious goals for AI safety and general progress 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) Strong candidates need not have: Experience in all of the above areas — we value breadth of interest and willingness to learn over checking every box Prior work specifically on language models or transformers; strong engineering fundamentals and ML knowledge transfer well An advanced degree — exceptional engineers with strong research instincts are equally encouraged to apply The annual compensation range for this role is listed below.  For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role. Annual Salary: £260,000 — £630,000 GBP Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices. Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this. We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other dom