AIML Sr Machine Learning Engineer, Responsible AI

Would you like to play a part in building the next generation of generative AI applications at Apple Were looking for Machine Learning Engineers to work on ambitious projects that will impact the future of Apple our products and the broader world. This role is directed at assessing quantifying and improving the safety and inclusivity of Apples Generative-AI powered features and products. nnIn this role youll have the opportunity to tackle innovative problems in machine learning particularly focused on large language models for text generation diffusion models for image generation and mixed model systems for multimodal applications. nAs a member of Apples Responsible AI group you will be working on a wide array of new features and research in the generative AI space. nOur team is currently interested in large generative models for vision and language with particular interest on Responsible AI safety fairness robustness explainability and uncertainty in

This role focuses on developing carrying-out interpreting and communicating pre- and post-ship evaluations of the safety of Apple Intelligence features. Both human grading and model-based auto-grading are thoughtfully leveraged to power these evaluations. Additionally this role researches and develops auto-grading methodology u0026 infrastructure to benefit ongoing and future Apple Intelligence safety safety evaluations that uphold Apples Responsible AI values requires thoughtful data sampling creation and curation for evaluation datasets; high quality detailed annotations and careful auto-grading to assess feature performance; and mindful analysis to understand what the evaluation means for the user experience. nnThis role heavily draws on applied data science scientific investigation and interpretation cross-functional communication and collaboration and metrics reporting and

Develop metrics for evaluation of safety and fairness risks inherent to generative AI datasets identify data needs and work on creative solutions scaling and expanding data coverage through human and synthetic generation auto-grading technologies and approaches for application in safety evaluations of generative AI technical direction and expertise to team-wide initiatives in safety and implement data pipelines and collaborate cross-functionally to execute end-to-end safety with highly-sensitive content with exposure to offensive and controversial

MS or PhD in Computer Science Machine Learning Statistics or related fields; or an equivalent qualification acquired through other working with generative models for evaluation and/or product development and up-to-date knowledge of common challenges and engineering skills and experience in writing production-quality code in experience in foundation model-based AI programming (i.e.: using DSPy for optimizing foundation model prompts for example) and a drive to innovate in this working with noisy crowd-based data labels and human

Experience working in the Responsible AI scientific research and publication organizational and operational skills working with large multi-functional and diverse about fairness and bias in generative AI systems and a strong desire to help make the technology more