Staff+ Software Engineer, Account Abuse (Machine Learning)

Job summary

Responsibilities

The Account Abuse team is tasked with ensuring Anthropic's computing capacity is allocated fairly, minimizing resources available to bad actors and preventing them from coming back. As a software engineer on this team, you will build the machine learning systems that help us detect and stop abuse…

• Build and operate a feature computation platform that serves both model training and real-time scoring, with point-in-time correct training data and low-latency online retrieval
• Train, evaluate, and deploy models that detect account-level abuse and fraud, running them both offline and online
• Build tooling that automates more of the model development lifecycle, including using Claude to speed up feature development, training, and evaluation
• Make backtesting, shadow deployment, and staged rollout the default path to production, with monitoring for training / serving skew, drift, and adversarial adaptation
• Work with our data scientists and our Policy & Enforcement team to improve label coverage and quality

What they're looking for

• Proficiency in Python and SQL
• Experience training machine learning models and deploying them to production
• Experience building data pipelines with a batch processing engine (e.g., Spark, Beam) and a workflow scheduler (e.g., Airflow)
• Working understanding of point-in-time correctness and training / serving skew, and how to prevent both
• Strong communication skills and ability to explain technical tradeoffs to non-technical stakeholders

Tech stack

• Python
• SQL
• Spark
• Airflow
• Kafka