About Anthropic
Anthropic’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.
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 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.
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
The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.
Annual Salary:
$340,000—$425,000 USD
Logistics
**Education requirements: We require at least a Bachelor's 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 aren't 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 you're interested in this work. We think AI systems like the ones we're 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 we're 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. We're 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 about our policy for using AI in our application process