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Machine Learning Systems Engineer, Research Tools

AnthropicSan Francisco, CA | New York City, NY | Seattle, WA
On-site Full-time

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Qualifications

The ideal candidate will possess extensive software engineering experience complemented by a solid understanding of machine learning principles. You should be adept at navigating complex and evolving research environments, demonstrating both independence and collaborative spirit in cross-functional team settings. A results-oriented mindset with a focus on flexibility and impact is essential. Proficiency in Python and familiarity with modern machine learning development practices are required, along with experience in machine learning systems, data pipelines, or ML infrastructure.

About the job

Join Anthropic as a Machine Learning Systems Engineer within our Encodings and Tokenization team, where you'll play a pivotal role in refining and optimizing our tokenization systems across Pretraining and Finetuning workflows. By bridging the gap between our Pretraining and Finetuning teams, you will help shape the essential infrastructure that enhances how our AI models learn from diverse data. Your contributions will be crucial in ensuring our AI systems remain reliable, interpretable, and steerable, driving forward our mission of developing beneficial AI technologies.

About Anthropic

Anthropic is dedicated to advancing the field of artificial intelligence while ensuring safety, reliability, and interpretability in AI systems. Our mission is to create AI technologies that are not only powerful but also beneficial for users and society at large. We are a rapidly growing team of passionate researchers, engineers, policy experts, and business leaders collaborating to build the next generation of trustworthy AI systems.

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