Staff Infrastructure Engineer, Pre-training

About Anthropic

Anthropics 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.

About the Role

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 Staff level Engineer to join our Pre-training team responsible for developing the next generation of large language 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.

Responsibilities

• Design and implement high-performance data processing infrastructure for large language model training
• Develop and maintain core processing primitives (e.g. tokenization deduplication chunking) with a focus on scalability
• Build robust systems for data quality assurance and validation at scale
• Implement comprehensive monitoring systems for data processing infrastructure
• Create and optimize distributed computing systems for processing web-scale datasets
• Collaborate with research teams to implement novel data processing architectures
• Build and maintain documentation for infrastructure components and systems
• Design and implement systems for reproducibility and traceability in data preparation

You may be a good fit if you have:

• 7 YOE outside of internships
• Strong software engineering skills with experience in building distributed systems
• Expertise in Python and Rust
• Hands-on experience with distributed computing frameworks particularly Apache Spark
• Deep understanding of cloud computing platforms and distributed systems architecture
• Experience with high-throughput fault-tolerant system design
• Strong background in performance optimization and system scaling
• Excellent problem-solving skills and attention to detail
• Strong communication skills and ability to work in a collaborative environment

• Advanced degree in Computer Science or related field
• Experience with language model training infrastructure
• Strong background in distributed systems and parallel computing
• Expertise in tokenization algorithms and techniques
• Experience building high-throughput fault-tolerant systems
• Deep knowledge of monitoring and observability practices
• Experience with infrastructure-as-code and configuration management
• Background in MLOps or ML infrastructure

Strong candidates may have:

• Have significant experience building and maintaining large-scale distributed systems
• Are passionate about system reliability and performance
• Enjoy solving complex technical challenges at scale
• Are comfortable working with ambiguous requirements and evolving specifications
• Take ownership of problems and drive solutions independently
• Are excited about contributing to the development of safe and ethical AI systems
• Can balance technical excellence with practical delivery
• Are eager to learn about machine learning research and its infrastructure requirements

Sample Projects

• Designing and implementing distributed computing architecture for web-scale data processing
• Building scalable infrastructure for model training data preparation
• Creating comprehensive monitoring and alerting systems
• Optimizing tokenization infrastructure for improved throughput
• Developing fault-tolerant distributed processing systems
• Implementing new infrastructure components based on research requirements
• Building automated testing frameworks for distributed systems

Logistics

Education requirements: We require at least a Bachelors degree in a related field or equivalent experience.

Location-based hybrid policy: Currently we expect all staff to be in one of our offices at least 25% of the time. However some roles may require more time in our offices.

Visa sponsorship:We do sponsor visas! However we arent able to successfully sponsor visas for every role and every candidate. But if we make you an offer we will make every reasonable effort to get you a visa and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy so we urge you not to exclude yourself prematurely and to submit an application if youre interested in this work. We think AI systems like the ones were building have enormous social and ethical implications. We think this makes representation even more important and we strive to include a range of diverse perspectives on our team.

How were different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact advancing our long-term goals of steerable trustworthy AI rather than work on smaller and more specific puzzles. We view AI research as an empirical science which has as much in common with physics and biology as with traditional efforts in computer science. Were an extremely collaborative group and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic including: GPT-3 Circuit-Based Interpretability Multimodal Neurons Scaling Laws AI & Compute Concrete Problems in AI Safety and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits optional equity donation matching generous vacation and parental leave flexible working hours and a lovely office space in which to collaborate with colleagues. Guidance on Candidates AI Usage:Learn aboutour policyfor using AI in our application process