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You'll work at the intersection of cutting-edge research and production engineering, implementing, scaling, and improving post-training techniques like Constitutional AI, RLHF, and other alignment methodologies.
Anthropic
This role lives at the boundary between research and engineering. You'll work across our entire production training stack: performance optimization, hardware debugging, experimental design, and launch coordination.
Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence.
You'll need to know accelerator performance well to turn it into tasks and signals models can learn from.
We're looking for Research Engineers to build the evaluations that tell us - and the world - what Claude can actually do.
The RL Velocity team owns the efficiency and reliability of our RL Science stack - the infrastructure, tooling, and systems that let researchers iterate quickly on training runs.
As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models.
We're seeking an exceptional Research Engineer to join our Life Sciences team at Anthropic.
We are looking for Research Engineers to help us redesign how Claude interacts with external data sources. Many of the paradigms for how data and knowledge bases are organized assume human consumers and constraints.
The Interpretability team at Anthropic is working to reverse-engineer how trained models work because we believe that a mechanistic understanding is the most robust way to make advanced systems safe.
As a Research Engineer on the Economic Research Data Platform team, you will design, build, and maintain critical infrastructure that powers Anthropic's research on AI's economic impact.
The Domain Scaling team has the goal to make Claude world-class at real-world knowledge work in domains like finance, healthcare, and legal.
As a Research Engineer on our team you will work end to end across the whole model stack, identifying and addressing key infra blockers on the path to scientific AGI.
This role blends research and engineering, requiring you to both develop novel approaches and realize them in code.
The Computer Use team focuses on teaching Claude to see, use, and understand computer interfaces.
This role blends research and engineering.
