About the role

What you’ll do

• Develop and productionize classification and evaluation capabilities
• Own classifiers across training, evaluation, deployment, and production inference
• Collaborate with researchers and engineers to deliver reliable feedback on model behavior at scale
• Reason about tradeoffs between quality, latency, and compute cost in production ML systems

What you’ll need

• Experience taking ML projects from problem formulation and experimentation through production deployment
• Strong foundations in supervised learning, statistics, and experimental design
• Practical experience evaluating models, investigating systematic errors, and working with imperfect labels
• Strong software engineering skills and the ability to build maintainable production ML systems
• Fluency in using AI agents to move quickly across multiple workstreams in a fast-paced environment
• Comfort working closely with researchers and engineers on open-ended problems

Original job description