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Anthropic
📍 San Francisco• $500K – $850K/yr
11mo ago

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. About the Role Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Staff level Engineer to join our Pre-training 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. Responsibilities Design and implement data processing infrastructure for large language model training (highly performant, reproducible, traceable) Develop and maintain core processing primitives (e.g., tokenization, deduplication, chunking) with a focus on scalability Build robust systems for data quality assurance and validation at scale Collaborate with research teams to implement novel data processing architectures Build and operate end-to-end data pipelines that turn raw web-scale corpora into training-ready datasets You may be a good fit if you have: 5+ YOE outside of internships Strong software engineering skills with experience building high-throughput fault-tolerant distributed systems Hands-on experience with distributed computing frameworks, particularly Apache Spark Excellent problem-solving skills and attention to detail Strong communication skills and ability to work in a collaborative environment Advanced degree in Computer Science or related field Experience with language model training infrastructure Background in Data Infrastructure, MLOps, or ML infrastructure Stro

pythonmachine learningartificial intelligence
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