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.
• Define safety policies and mitigation strategies for large language and multimodal models.
• Provide technical direction for dataset design and safety alignment strategies.
• Oversee the implementation of mitigation architectures in production environments.
• Analyze evaluation results and conduct failure investigations to improve feature safety.
• Translate complex technical insights into actionable recommendations for senior leadership and cross-functional partners.
• Mentor and develop a high-performing team while fostering a culture of technical excellence.
• Interpret human and automated feedback to inform product shipping decisions.

What we're looking for

• 5+ years of experience in machine learning, including work with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision.
• 2+ years of experience directly managing engineering teams.
• Proficiency in Python and data science libraries like Pandas for analysis and ML workflows.
• Experience collecting and analyzing language, vision, or multimodal datasets.
• Background in failure analysis, quality engineering, or robustness testing for ML-driven systems.
• Ability to interpret outputs from human and automated evaluations of complex or multi-labeled data.
• Proven ability to translate complex technical insights for cross-functional partners and senior leadership.
• A BS, MS, or PhD in Computer Science, Machine Learning, or a related field is preferred.