Research Engineer, Science of Scaling

<div class="content-intro"><h2><strong>About Anthropic</strong></h2> <p>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.</p></div><p class="p2"><strong>About the role</strong></p> <p class="p2">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.</p> <p class="p2"><strong>Responsibilities:</strong></p> <ul class="ul1"> <li class="li2">Conduct research intro the science of converting compute into intelligence</li> <li class="li2">Independently lead small research projects while collaborating with team members on larger initiatives</li> <li class="li2">Design, run, and analyze scientific experiments to advance our understanding of large language models</li> <li class="li2">Optimize training infrastructure to improve efficiency and reliability</li> <li class="li2">Develop dev tooling to enhance team productivity</li> </ul> <p class="p2"><strong>You may be a good fit if you:</strong></p> <ul class="ul1"> <li class="li2">Have significant software engineering experience and a proven track record of building complex systems</li> <li class="li2">Hold an advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field</li> <li class="li2">Are proficient in Python and experienced with deep learning frameworks</li> <li class="li2">Are results-oriented with a bias towards flexibility and impact</li> <li class="li2">Enjoy pair programming and collaborative work, and are willing to take on tasks outside your job description to support the team</li> <li class="li2">View research and engineering as two sides of the same coin, seeking to understand all aspects of the research program to maximize impact</li> <li class="li2">Care about the societal impacts of your work and have ambitious goals for AI safety and general progress</li> </ul> <p class="p2"><strong>Strong candidates may have:</strong></p> <ul class="ul1"> <li class="li2">Experience with JAX</li> <li class="li2">Experience with reinforcement learning</li> <li class="li2">Experience working on high-performance, large-scale ML systems</li> <li class="li2">Familiarity with accelerators, Kubernetes, and OS internals</li> <li class="li2">Experience with language modeling using transformer architectures</li> <li class="li2">Background in large-scale ETL processes</li> <li class="li2">Experience with distributed training at scale (thousands of accelerators)</li> </ul> <p class="p2"><strong>Strong candidates need not have:</strong></p> <ul class="ul1"> <li class="li2">Experience in all of the above areas — we value breadth of interest and willingness to learn over checking every box</li> <li class="li2">Prior work specifically on language models or transformers; strong engineering fundamentals and ML knowledge transfer well</li> <li class="li2">An advanced degree — exceptional engineers with strong research instincts are equally encouraged to apply</li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p>The annual compensation range for this role is listed below. </p> <p>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.</p></div><div class="title">A ... (truncated, view full listing at source)