About AnthropicAnthropic'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.
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 Research Engineer to join our Pretraining 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.
Key ResponsibilitiesDesign and implement high-performance data processing infrastructure for large language model trainingDevelop and maintain core processing primitives (e.g., tokenization, deduplication, chunking) with a focus on scalabilityBuild robust systems for data quality assurance and validation at scaleImplement comprehensive monitoring systems for data processing infrastructureCreate and optimize distributed computing systems for processing web-scale datasetsCollaborate with research teams to implement novel data processing architecturesBuild and maintain documentation for infrastructure components and systemsDesign and implement systems for reproducibility and traceability in data preparationQualificationsStrong software engineering skills with experience in building distributed systemsExpertise in Python and experience with distributed computing frameworksDeep understanding of cloud computing platforms and distributed systems architectureExperience with high-throughput, fault-tolerant system designStrong background in performance optimization and system scalingExcellent problem-solving skills and attention to detailStrong communication skills and ability to work in a collaborative environmentPreferred ExperienceAdvanced degree (MS or PhD) in Computer Science or related fieldExperience with language model training infrastructureStrong background in distributed systems and parallel computingExpertise in tokenization algorithms and techniquesExperience building high-throughput, fault-tolerant systemsDeep knowledge of monitoring and observability practicesExperience with infrastructure-as-code and configuration managementBackground in MLOps or ML infrastructureYou'll thrive in this role if youHave significant experience building and maintaining large-scale distributed systemsAre passionate about system reliability and performanceEnjoy solving complex technical challenges at scaleAre comfortable working with ambiguous requirements and evolving specificationsTake ownership of problems and drive solutions independentlyAre excited about contributing to the development of safe and ethical AI systemsCan balance technical excellence with practical deliveryAre eager to learn about machine learning research and its infrastructure requirementsSample ProjectsDesigning and implementing distributed computing architecture for web-scale data processingBuilding scalable infrastructure for model training data preparationCreating comprehensive monitoring and alerting systemsOptimizing tokenization infrastructure for improved throughputDeveloping fault-tolerant distributed processing systemsImplementing new infrastructure components based on research requirementsBuilding automated testing frameworks for distributed systemsAt Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.
If you're excited about pushing the boundaries of AI while prioritizing safety and ethics, we want to hear from you!
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