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 robust safety policies and mitigation strategies in collaboration with legal, design, and engineering teams.
• Provide technical direction for dataset design and safety alignment strategies for large language and multimodal models.
• Oversee the implementation of mitigation architectures and conduct failure investigations for production systems.
• Analyze evaluation results from human and automated feedback to improve feature safety and user trust.
• Translate complex technical insights into actionable recommendations for senior leadership and cross-functional partners.
• Build, mentor, and develop a high-performing engineering team in a fast-paced environment.

What we're looking for

• 5+ years of experience in machine learning, including work with generative models, 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, multi-labeled data.
• Proven ability to communicate technical insights to cross-functional partners and senior leadership.
• BS, MS, or PhD in Computer Science, Machine Learning, or a related field.