Machine Learning Infrastructure Engineer, Safeguards Research

Anthropic's Safeguards team builds systems to detect and mitigate misuse of AI models. We're seeking a Machine Learning Infrastructure Engineer to own the infrastructure behind this research, focusing on scaling, reliability, and efficiency.

Key responsibilities:

• Build and scale infrastructure and data pipelines for Safeguards machine learning research
• Own training, evaluation, and scoring workflows, optimizing the time between idea and result
• Design tooling and interfaces for researchers to use directly
• Implement correctness and sanity checking to ensure trustworthy results
• Transition high-value research workflows from experiments to production-grade jobs
• Improve throughput, cost, and reliability of large-scale inference and scoring workloads
• Collaborate with researchers and engineers to understand and anticipate workflow needs

Requirements:

• Strong software engineering fundamentals and hands-on coding ability in Python
• Experience with data-intensive or distributed systems in production
• Experience building tooling or infrastructure for engineers or researchers
• Comfort working across the research-to-deployment pipeline
• Ability to debug performance and correctness problems
• Strong written and verbal communication skills

Preferred qualifications:

• Experience with high-performance, large-scale machine learning systems
• Familiarity with language modeling and transformers
• Experience with machine learning framework internals, GPU programming, or inference optimization
• Experience building experiment tracking, caching layers, or evaluation harnesses
• Interest in AI system misuse risks and mitigation

The annual compensation range for this role is $350,000-$500,000 USD.