Anthropic
Data Infrastructure Engineer, Pre-training
About this role
Anthropic seeks a Staff-level Data Infrastructure Engineer to design and build scalable data processing systems for large language model pre-training. You'll develop high-performance, fault-tolerant pipelines that transform raw web-scale data into training-ready datasets while collaborating closely with research teams.
What you'll do
- Design and implement high-performance, reproducible data processing infrastructure for LLM training
- Develop core processing primitives such as tokenization, deduplication, and chunking at scale
- Build data quality assurance and validation systems for web-scale datasets
- Collaborate with researchers to implement novel data processing architectures
- Build and operate end-to-end data pipelines from raw corpora to training-ready formats
What they're looking for
- Distributed systems design and implementation
- Apache Spark and distributed computing frameworks
- Python and Rust programming
- High-throughput, fault-tolerant system architecture
- Data pipeline development and optimization
- ML infrastructure and MLOps experience
- Problem-solving and system reliability focus
- Ability to work with ambiguous requirements
Benefits
- Work on cutting-edge AI safety and alignment research
- Contribute to development of safe and ethical AI systems
- Competitive annual compensation ($500,000–$850,000)
- Visa sponsorship available
- Hybrid work arrangement (minimum 25% office time)
- Collaborative environment with researchers and engineers
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Anthropic
Anthropic builds Claude, an AI assistant, and is hiring for engineering roles across infrastructure, data systems, and security that support both AI research operations and the company's internal technology needs. The company seeks infrastructure engineers, systems integrators, data scientists, and security specialists to build production-scale systems for training data pipelines, financial operations, developer productivity measurement, research infrastructure, and server firmware security.
- Website
- anthropic.com
Likely interview questions
- Describe your experience building fault-tolerant distributed systems. What challenges did you face and how did you solve them?
- How have you optimized data processing pipelines for throughput and reliability at scale?