Data Infrastructure Engineer, Pre-training

Uncover; San Francisco, Northern (CA, KY); Hybrid; USD 500,000 - 850,000; Full time

Benefits offered by this job

Visa sponsorship

Equity donation matching

Flexible working hours

Generous vacation and parental leave

Lovely SF office space

Job summary

Anthropic is seeking a Staff level Engineer to join its Pre-training team. You will design data processing infrastructure for large language model training and build scalable, fault-tolerant systems.

Join a team dedicated to safe, steerable AI and work across research and engineering to advance training data pipelines and model infrastructure in a hybrid SF office.

Qualifications

• 5+ years of experience outside internships.
• Strong software engineering skills building high-throughput fault-tolerant distributed systems.
• Experience with distributed computing frameworks, particularly Apache Spark.
• Excellent problem-solving and attention to detail.
• Strong communication and collaboration skills.
• Advanced degree in Computer Science or related field.
• Experience with language model training infrastructure.

Responsibilities

• Design and implement data processing infrastructure for large language model training.
• Develop and maintain core processing primitives with a focus on scalability.
• Build robust systems for data quality assurance and validation at scale.
• Collaborate with research teams to implement data processing architectures.
• Build and operate end-to-end data pipelines turning raw corpora into training-ready datasets.

Skills

Distributed systems

Spark

Python

Rust

Collaboration

Education

Bachelor’s degree in Computer Science or related field

Advanced degree in Computer Science

Tools

Apache Spark

Job description

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 a 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 data processing infrastructure for large language model training (highly performant, reproducible, traceable)
• 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
• 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

Qualifications

• 5+ YOE outside of internships
• Strong software engineering skills with experience building high‑throughput fault‑tolerant distributed systems
• Hands‑on experience with distributed computing frameworks, particularly Apache Spark
• 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
• Background in Data Infrastructure, MLOps, or ML infrastructure

Strong candidates may have

• Have significant experience building high‑throughput fault‑tolerant distributed systems
• Expertise with Python and Rust
• Passionate about system reliability and performance
• 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
• Developing fault‑tolerant distributed processing systems
• Implementing new infrastructure components based on research requirements

Compensation

Annual Salary: $500,000 — $850,000 USD

Logistics

• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• 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. Your safety matters to us.

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.