Research Engineer

About the role:

As a Research Engineer on the Clio team, you'll be responsible for maintaining and enhancing the critical infrastructure that powers Anthropic's research efforts. You'll work with systems that process data at large scales and serve many internal teams across the organization. Your work will directly enable researchers, safety teams, and other colleagues to achieve their goals by ensuring our research tools are reliable, efficient, and privacy-preserving.

In this role, you'll collaborate extensively with teams across Anthropic—from Finetuning, RL Research, and Societal Impacts to Safeguards, Communications, and customer success—to understand their diverse needs and translate them into robust technical solutions. You'll be responsible for the full lifecycle of research tools, from enhancing monitoring capabilities to improving user interfaces, all while maintaining the highest standards for data privacy and system reliability.

Responsibilities:

• Enable Anthropic researchers to analyze large sets of Claude usage while preserving user privacy.
• Maintain systems that perform challenging dataset clustering and hierarchy-building.
• Debug data processing pipelines that may encounter difficult issues, such as concurrency inefficiencies or errors obscured by inter-process communications.
• Implement monitoring systems for tools that process large datasets.
• Work with internal users across teams to understand their needs and prioritize fixes and features.
• Work toward intuitive interfaces — both command-line and frontend — for research tools.
• Optimize research tools for speed and efficient resource usage.
• Enhance user data privacy protections, ensuring clear and auditable data handling practices.
• Write and maintain related documentation.

You may be a good fit if you:

• Have 5+ years of software engineering experience with a track record of building and maintaining production systems; note that a machine learning-specific background is not critical
• Are highly proficient in Python
• Have experience with data infrastructure and large datasets in production environments
• Are comfortable working independently while maintaining collaborative relationships across teams
• Have excellent communication skills and enjoy working with diverse stakeholders to understand and solve their technical challenges
• Have experience with cloud infrastructure platforms such as AWS or GCP
• Think naturally in terms of helping move the entire organization forward, even when that means taking on work outside your primary responsibilities
• Are committed to developing AI systems responsibly and care about the societal impacts of your work

Strong candidates may also have experience with:

• High-performance, large-scale ML systems and distributed computing
• Kubernetes and container orchestration platforms
• GPU computing and optimization for specialized hardware
• Highly concurrent systems
• Productizing research tools and transitioning from research prototypes to production systems
• Privacy-preserving technologies and secure data handling practices

Deadline to apply: None. Applications will be reviewed on a rolling basis.