Research Engineer, Data Infra

As a Research Engineer, Data Infra at Anthropic, you will design and implement high-performance data processing infrastructure specifically for large language model training. Your role involves creating core processing primitives like tokenization and chunking, as well as building robust data quality assurance systems. Additionally, collaboration with research teams to implement novel data processing architectures is central to the position, ensuring the development of safe and trustworthy AI systems.

To qualify for the Research Engineer, Data Infra position at Anthropic, you should have at least 5 years of experience outside of internships, expertise in software engineering, and a strong understanding of distributed systems architecture. Proficiency in Python and familiarity with cloud computing platforms are essential, along with experience in designing fault-tolerant systems. An advanced degree in Computer Science is preferred but not mandatory.

In this role, you'll engage in exciting projects like designing distributed computing architecture for web-scale data processing, building scalable infrastructure for model training, and developing fault-tolerant processing systems. You'll also optimize tokenization infrastructure and implement comprehensive monitoring systems, directly impacting the development of safe AI systems.

Yes, Anthropic does sponsor visas for the Research Engineer, Data Infra role, provided all reasonable efforts are made to assist with your visa application. While not every application may be successful, the company is committed to supporting candidates through the immigration process.

The expected annual salary range for the Research Engineer, Data Infra position at Anthropic is between $315,000 and $425,000 USD. This competitive compensation reflects the level of expertise and commitment we seek in candidates as we advance the frontiers of AI together.

In responding to this question, detail specific projects where you designed or worked on distributed systems. Highlight your role, the technologies used, and any challenges you overcame during the project. Emphasize how your contributions led to the success of the project, focusing on scalability and performance.

To answer this effectively, provide a concrete example of a project where you implemented performance optimizations. Discuss the methods you used to identify bottlenecks and the tools or techniques applied to improve system efficiency, always connecting your experience to the role of a Research Engineer at Anthropic.

Discuss your experience with specific cloud services and how you utilized them for distributed processing or data storage. Highlight any challenges faced and how you managed to leverage cloud resources for scalable solutions. This experience underscores your understanding of cloud infrastructure, which is vital for the Research Engineer position.

Emphasize your approach to implementing data validation and monitoring systems, perhaps mentioning specific tools you've used. Show your understanding of the importance of data quality in AI systems, as this will resonate well with Anthropic’s goals in building trustworthy AI solutions.

In this response, detail an instance where you worked with researchers to develop or implement a new data processing architecture. Talk about the collaborative dynamics, how communication played a role, and the ultimate success of the project, reinforcing the importance of teamwork in the Research Engineer role.

Mention specific resources you follow, such as research papers, online courses, or forums. Discuss how you incorporate ongoing learning into your routine and share any recent trends in AI that you find particularly interesting, demonstrating your commitment to staying informed in this rapidly evolving field.

Share insights into the tools you have used, like Terraform or Ansible, and describe a project where infrastructure-as-code improved project deployments or workflows. Your familiarity with these practices can set you apart as a suitable candidate for the technical demands of the Research Engineer role at Anthropic.

Talk about your approach to identifying key stakeholders and your strategies for clarifying requirements through discussions and feedback loops. Providing an example of a time you successfully managed ambiguity will highlight your problem-solving capabilities, which are essential for the role.

Express your passion for ethical AI, emphasizing the importance of creating technology that aligns with human interests. Share your views on social responsibility within the tech industry, and perhaps reference specific initiatives or projects that inspire you, aligning your sentiment with Anthropic's mission.

Provide a detailed account of the issue, your analysis process, the steps you took to solve it, and the positive outcomes that emerged, such as improved system performance or reliability. This response can showcase your critical thinking and engineering skills, both vital for a Research Engineer at Anthropic.