Job Description

Locations

• Cupertino, California, United States 95014

Salary

Skills Required

• Machine Learning Engineeringintermediate
• Responsible AIintermediate
• Risk Assessmentintermediate
• Policy Definitionintermediate
• Mitigation Strategy Developmentintermediate
• Continuous Improvementintermediate
• Model Evaluationintermediate
• Model Alignmentintermediate
• Safety Monitoringintermediate
• Large Language Modelsintermediate
• Multimodal Modelsintermediate
• Cross-functional Collaborationintermediate
• Fairness Researchintermediate
• Robustness Researchintermediate
• Uncertainty Researchintermediate
• Safety Researchintermediate
• Safety Policy Definitionintermediate
• Architecting Mitigation Strategiesintermediate
• Safety Alignment Strategiesintermediate
• Model Developmentintermediate
• Tool Developmentintermediate
• Dataset Developmentintermediate
• Evaluation Methods Developmentintermediate
• Failure Diagnosisintermediate
• Human Feedback Incorporationintermediate
• Automated Feedback Incorporationintermediate

Required Qualifications

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

Preferred Qualifications

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

Responsibilities

• - 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

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