Machine Learning Infrastructure Engineer (Safeguards Research)

Join Anthropic's Safeguards team as a Machine Learning Infrastructure Engineer. You will be responsible for building and scaling the infrastructure and data pipelines behind Safeguards machine learning research. This role requires a strong background in solving large-scale systems and data problems, as well as a desire to grow deep machine learning expertise. You will work closely with researchers and engineers to understand their workflows and anticipate their needs.

• Construire et mettre à l'échelle l'infrastructure et les pipelines de données derrière la recherche en apprentissage automatique des Safeguards.
• Posséder les workflows d'entraînement, d'évaluation et de scoring que les chercheurs utilisent, en mettant l'accent sur la réduction du temps entre une idée et un résultat.
• Collaborer étroitement avec les chercheurs et les ingénieurs pour comprendre leurs workflows, anticiper leurs besoins et concevoir en conséquence.
• Comfort working across the research-to-deployment pipeline, from exploratory experiments to production systems
• Experience building and operating data-intensive or distributed systems in production
• Strong software engineering fundamentals and hands-on coding ability, with proficiency in Python
• Ability to debug performance and correctness problems across an unfamiliar stack
• Experience building tooling or infrastructure that other engineers or researchers use as a dependency
• Strong written and verbal communication skills, and a collaborative approach to technical decisions
• Experience building experiment tracking, caching layers, or evaluation harnesses for research teams
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Experience with machine learning framework internals, GPU or accelerator programming, or inference optimization
• Experience with high-performance, large-scale machine learning systems
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Familiarity with language modeling and transformers, including working with model internals
• Interest in the misuse risks of AI systems and a desire to work on mitigating them
• Experience with probes, interpretability, or classifier development