仕事内容
<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><h2 class="heading"><strong>About the role</strong></h2>
<p>Anthropic's production models undergo sophisticated post-training processes to enhance their capabilities, alignment, and safety. As a Research Engineer on our Post-Training team, you'll train our base models through the complete post-training stack to deliver the production Claude models that users interact with.</p>
<p>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. Your work will directly impact the quality, safety, and capabilities of our production models.</p>
<p><em>Note: For this role, we conduct all interviews in Python. This role may require responding to incidents on short-notice, including on weekends.</em></p>
<h2 class="heading"><strong>Responsibilities:</strong></h2>
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<p>Implement and optimize post-training techniques at scale on frontier models</p>
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<p>Conduct research to develop and optimize post-training recipes that directly improve production model quality</p>
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<p>Design, build, and run robust, efficient pipelines for model fine-tuning and evaluation</p>
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<p>Develop tools to measure and improve model performance across various dimensions</p>
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<p>Collaborate with research teams to translate emerging techniques into production-ready implementations</p>
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<p>Debug complex issues in training pipelines and model behavior</p>
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<p>Help establish best practices for reliable
求めるスキル
Python
LLM
RLHF
LoRA
AWS
Rust