AIML - Senior ML Engineer, Responsible AI and Safety

Responsibilities: Lead end-to-end responsible AI lifecycle: assess risks, define policies, build mitigation strategies, and drive continuous improvements Collaborate with leadership, engineering, legal, and regulatory teams to shape safety policies and safeguard product innovation Develop architecture mitigation and safety alignment strategies for generative models and oversee production integration Create models, tools, datasets, and evaluation methods to monitor and diagnose failures across deployment Incorporate human and automated feedback post-launch to improve feature safety and user trust Perform failure analysis, robustness testing, and data analysis on language, vision, or multimodal datasets

Key requirements: 3+ years of ML experience with generative models (Transformers, LLMs, VLMs), NLP, or Computer Vision Proficiency in Python and data science libraries (e.g., Pandas) with strong data analysis and ML workflow skills Excellent communication to translate technical insights for cross-functional partners and executives Strong analytical and problem-solving abilities in ambiguous contexts Experience designing and supporting human and automated evaluations for complex 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 Comfort with sensitive or potentially offensive content cross-functional collaboration clear communication analytical thinking Transformers LLMs VLMs