Senior Machine Learning Engineering Manager, Responsible AI and Safety

What you'll do

• Lead a team of machine learning engineers to manage the end-to-end responsible AI lifecycle for generative features.
• Define robust safety policies and technical directions for dataset design and safety alignment strategies.
• Oversee the implementation of end-to-end mitigation architectures in production environments.
• Analyze evaluation results and conduct failure investigations to improve feature safety and user trust.
• Interpret outputs from human and automated evaluations to inform mitigation improvements and shipping decisions.
• Partner with cross-functional teams to minimize unintended consequences across people, systems, and society.
• Mentor and develop a high-performing engineering team while fostering a culture of technical excellence.
• Provide safety recommendations and technical insights to senior leadership and executive partners.

What we're looking for

• 5+ years of experience in machine learning, including generative models, NLP, or Computer Vision.
• 2+ years of experience directly managing engineering teams.
• Proficiency in Python and data science libraries with strong skills in data analysis and applied ML workflows.
• Proven track record of leading technical teams through ambiguity to deliver high-impact results.
• Experience collecting and analyzing language, vision, or multimodal datasets.
• Background in failure analysis, quality engineering, or robustness testing for ML-driven systems.
• Excellent communication skills to translate complex technical insights for cross-functional partners and senior leadership.
• BS, MS, or PhD in Computer Science, Machine Learning, or related field (preferred).