Teams at Anthropic

Four-month, full-time research fellowship focused on ML systems and performance. Fellows build and evaluate infrastructure-heavy projects (e.g., CPU simulators, accelerator backends, large-scale distributed training), use external models/APIs, receive mentorship, funding for compute, and aim to produce public research outputs.

Four-month full-time research fellowship mentoring fellows to run empirical RL and LLM projects using external infrastructure. Fellows receive compute funding and a weekly stipend, produce public outputs (e.g., papers), and work on RL environments, algorithms, model fine-tuning, and training/evaluation of large models with mentor support.

4-month full-time funded research fellowship using external models/APIs to produce public outputs (papers). Fellows receive mentorship, workspace access (Berkeley or London) or remote options within US/UK/Canada, weekly stipend, compute funding, and are expected to implement experiments, collaborate with mentors, and communicate results. Applicants must be fluent in Python and authorized to work in the US, UK, or Canada.