ML Engineer, Responsible AI and Safety

What you'll do

• Design, build, and deploy production-grade ML models to detect abuse across text, image, and audio modalities.
• Manage the full machine learning lifecycle from initial prototyping and data analysis to deployment and monitoring.
• Develop and implement data strategies including synthetic data pipelines and automated annotation systems.
• Architect end-to-end systems for real-time monitoring of platform activity and automated enforcement actions.
• Translate adversarial insights into production-ready code to defend against emerging security threats.
• Fine-tune and align large language models specifically for safety and security applications.
• Build large-scale data processing pipelines and machine learning infrastructure.

What we're looking for

• At least 2 years of experience shipping machine learning models to production and owning the full lifecycle from development to maintenance.
• Strong familiarity with research fundamentals, machine learning principles, and methodologies regarding LLMs, foundation models, and diffusion models.
• Proficiency in Python and deep learning toolkits such as JAX, PyTorch, or TensorFlow.
• Ability to work with sensitive and offensive content for security and abuse detection systems.
• BS, MS, or PhD in Computer Science, Machine Learning, or a related field.
• Hands-on experience fine-tuning or aligning large language models for security or safety applications.
• Experience building large-scale data processing pipelines and machine learning infrastructure.
• Experience leading technical projects and collaborating with diverse, cross-functional teams.