Machine Learning Engineer, Safety

Job Description

The Machine Learning Engineer, Safety at xAI joins the Applied Safety team to build ML systems that ensure compliance with X’s Terms of Service and enhance user safety. The role owns the end-to-end ML lifecycle to detect and mitigate threats such as abuse, spam, and fraud, integrating advanced ML (including LLM-based techniques) into high-throughput production systems. Ideal candidates thrive in 0-to-1 environments, prioritize impactful code over documentation, and are comfortable tackling high-stakes safety challenges.

Responsibilities

• Own end-to-end ML lifecycle for safety systems: data gathering, cleaning, model training, evaluation, and large-scale serving.
• Develop ML models to detect and remediate violative content (abuse, spam, child safety, etc.).
• Integrate models into production systems for real-time, high-throughput inference.
• Lead technical initiatives in ML-driven areas such as fraud detection or content moderation.
• Collaborate closely with engineering, product, and operations to improve the safety ecosystem.
• Invent novel ML solutions in uncharted safety spaces and 0-to-1 product areas.

Benefits