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AIML - Tech Lead ML Engineer, Responsible AI

3 days ago Cupertino, CA

Join Us in Shaping the Future of Generative AI at Apple!

Are you passionate about making AI systems safer, more inclusive, and globally representative? Apple is seeking an expert Machine Learning Engineer to shape the future of responsible AI for the next generation of generative features.

In this role, you will lead the responsible AI lifecycle end-to-end: assessing risks, defining policies, developing mitigation strategies, and driving continuous improvements. Your work will directly influence how we evaluate, align, and monitor the safety of large language and multimodal models.

As part of Apple's Responsible AI group within the Human-Centered Machine Intelligence (HCMI) organization, you'll collaborate with cross-functional partners to minimize unintended consequences across people, systems, and society while elevating feature capabilities and the overall user experience. Together, we'll anticipate challenges, measure real-world impact, and deliver trusted, high-quality AI experiences to users around the globe. You'll also contribute to forward-looking research in fairness, robustness, uncertainty, and safety - pushing the boundaries of responsible AI at scale.

Description

- Lead Responsible AI efforts for a global generative AI product in a highly cross-functional environment

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- 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

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

Minimum Qualifications

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

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .

Client-provided location(s): Cupertino, CA
Job ID: apple-200619777-0836_rxr-658
Employment Type: OTHER
Posted: 2025-11-10T19:05:25

Perks and Benefits

  • Health and Wellness

    • Parental Benefits

      • Work Flexibility

        • Office Life and Perks

          • Vacation and Time Off

            • Financial and Retirement

              • Professional Development

                • Diversity and Inclusion

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