Requirements

3+ years of proven ability in machine learning, including work with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision
Proficiency in Python and data science libraries (e.g. Pandas) with strong skills in data analysis, visualization, and applied ML workflows
Excellent interpersonal skills and proven ability to translate sophisticated technical insights for cross‑functional partners, senior leadership, and executives
Strong analytical and independent problem-solving skills, with ability to navigate ambiguity
Experience designing and supporting human and automated evaluations, particularly with complex, nuanced, or multi‑labeled data
Hands‑on experience collecting and analyzing language, vision, or multimodal datasets
Background in failure analysis, quality engineering, or robustness testing for ML‑driven systems
Comfortable working with sensitive or potentially offensive content

Preferred Qualifications

BS, MS, or PhD in Computer Science, Machine Learning, or related field, or equivalent experience
Proven success contributing in a highly cross‑functional environment
Experience shipping complex AI systems at global scale
Background in model explainability, uncertainty estimation, or interpretability
Curiosity and research interest in fairness, bias, and the societal impacts of generative AI
Passion for building innovative, high‑impact products that draw upon interdisciplinary skills

Lead Responsible AI efforts for a global generative AI product in a highly cross-functional environment
Define safety policies in collaboration with leadership, design, engineering, legal, and regulatory teams, ensuring alignment with product goals
Architect mitigation and safety alignment strategies for generative models and drive integration in production
Develop models, tools, datasets, and evaluation methods to monitor, diagnose failures, and improve the safety of generative models throughout the model deployment lifecycle
Incorporate human and automated feedback post‑launch to continuously improve feature safety and user trust

Collaborate with cross-functional partners to minimize unintended consequences across people, systems, and society
Contribute to forward‑looking research in fairness, robustness, uncertainty, and safety
Deliver trusted, high‑quality AI experiences to users around the globe