Research Engineer / Research Scientist, Tokens

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. You want to build large scale ML systems from the ground up. You care about making safe, steerable, trustworthy systems. As a Research Engineer, you'll touch all parts of our code and infrastructure, whether that includes making the cluster more reliable for our big jobs, improving throughput and efficiency, running and designing scientific experiments, or improving our dev tooling. You're excited to write code when you understand the research context and the broader importance. You May Be a Good Fit If You Have significant software engineering experience Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to learn more about machine learning research Care about the societal impacts of your work Strong Candidates May Also Have Experience With High performance, large-scale ML systems GPUs, Kubernetes, Pytorch, or OS internals Language modeling with transformers Reinforcement learning Large-scale ETL Representative Projects Optimizing the throughput of a new attention mechanism Comparing the compute efficiency of two Transformer variants Making a Wikipedia dataset in a format models can easily consume Scaling a distributed training job to thousands of GPUs Writing a design doc for fault tolerance strategies Creating an interactive visualization of attention between tokens in a language model Annual Salary

$350,000—$500,000 USD

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 sponsor visas. Benefits We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. #J-18808-Ljbffr Anthropic