Director of Safety ML

Responsibilities

• Set the vision and strategy for applying ML to Trust & Safety, ensuring scalable, proactive protection against evolving abuse patterns.
• Lead and grow a high-performing Safety ML organization, including applied research, model development, productionization, and continuous improvement.
• Develop and deploy cutting-edge Safety ML systems (including fine-tuned LLMs and transformer models) that outperform state-of-the-art solutions in quality, latency, and efficiency.
• Partner with Trust & Safety, Product, Moderation, and AI/ML Platform teams to identify safety risks, emerging harm vectors, and ML opportunities that improve detection, enforcement, and user experience.
• Drive successful experimentation, evaluation, and model lifecycle management, ensuring high precision, recall, explainability, and policy alignment.
• Champion ethical and responsible AI practices in all Safety ML solutions.
• Track performance through metrics, research-based iteration, and alignment with Reddit’s safety policies and regulatory standards.
• Represent Safety ML leadership internally and externally — including conferences, publications, industry groups, and cross-company collaboration initiatives.

Required Qualifications

• 10+ years of experience in Machine Learning, AI, or applied research, with a strong background in Trust & Safety, abuse prevention, detection, or content integrity.
• 5+ years of experience leading multi-disciplinary ML teams of 25+ team members (applied science, engineering, analytics) in a high-growth or high-impact environment. Must have experience managing people leaders (managers with direct reports)
• Proven track record of shipping ML systems at scale in production, ideally including transformer-based models and LLM fine-tuning.
• Depth in NLP, content understanding, detection systems, supervised and weak-supervision techniques.
• Strong cross-functional leadership skills, with ability to influence executives and foster alignment across Safety, Product, and Engineering.
• Thought leadership in responsible AI, safety ML research, or safety measurement frameworks.
• Entrepreneurial mindset — experience founding or scaling a product or ML org.

Nice to Have

• Experience building or operating real-time abuse detection and automated moderation systems in a complex user-generated content ecosystem.
• Prior work in consumer-facing tech, social platforms, or large-scale community-driven products.