Staff Pre-Training Data Infrastructure Engineer

Anthropic; San Francisco (CA); On-site; USD 500,000 - 850,000; Full time

Job summary

Anthropic is seeking a Staff-level Engineer for the Pre-training team to advance the next generation of large language models. You will design scalable data processing infrastructures, implement data quality systems, and collaborate with research teams to turn web-scale data into training-ready datasets.

Strong background in distributed systems, Spark, and ML infrastructure is essential. The role requires 5+ years of experience outside internships, advanced CS education, and a passion for safe,

Qualifications

• 5+ years outside internships
• Experience building high-throughput fault-tolerant distributed systems
• Hands-on experience with distributed computing frameworks, especially Apache Spark
• Excellent problem-solving and attention to detail
• Strong communication skills and collaboration in teams
• Advanced degree in Computer Science or related field
• Experience with language model training infrastructure
• Background in Data Infrastructure, MLOps, or ML infrastructure

Responsibilities

• Design and implement data processing infrastructure for large language model training (highly performant, reproducible, traceable)
• Develop and maintain core processing primitives (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

Skills

Distributed systems

Python

Rust

Data infrastructure

MLOps

Language model training

Strong communication

Problem solving

Education

Advanced degree in Computer Science or related field

Bachelor’s degree in a relevant field

Tools

Apache Spark

Job description

Anthropic is seeking a Staff-level Engineer for the Pre-training team to advance the next generation of large language models. You will design scalable data processing infrastructures, implement data quality systems, and collaborate with research teams to turn web-scale data into training-ready datasets.

Strong background in distributed systems, Spark, and ML infrastructure is essential. The role requires 5+ years of experience outside internships, advanced CS education, and a passion for safe,