Senior ML Infrastructure Engineer

Anthropic is seeking a Senior ML Infrastructure Engineer to build and maintain the robust, scalable infrastructure required to train and deploy our state-of-the-art AI systems, including our large language models. You will be instrumental in ensuring our ML workflows are efficient, reliable, and can handle massive computational demands. **Responsibilities:** * Design, develop, and maintain scalable ML infrastructure, including distributed training systems, data pipelines, and model serving frameworks. * Optimize infrastructure for performance, cost, and reliability. * Collaborate with ML researchers and engineers to understand their infrastructure needs and provide effective solutions. * Implement best practices for MLOps, including CI/CD, monitoring, and version control for ML models and data. * Troubleshoot and resolve complex infrastructure issues. **Minimum Qualifications:** * Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. * 5+ years of experience in software engineering, with a significant focus on infrastructure or ML infrastructure. * Strong proficiency in Python and experience with cloud platforms (AWS, GCP, or Azure). * Experience with containerization technologies (Docker, Kubernetes). * Familiarity with distributed computing frameworks (e.g., Ray, Spark) and ML frameworks (e.g., PyTorch, TensorFlow). **Preferred Qualifications:** * Master's degree or PhD in a relevant field. * Experience with large-scale ML training infrastructure. * Deep understanding of GPU computing and optimization. * Experience building and managing CI/CD pipelines for ML systems. Anthropic offers competitive compensation, generous benefits, and the opportunity to work on safety-critical AI research and development.