AIML - Machine Learning Engineer, Evaluation - Responsible AI and Safety

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 experienced Senior Machine Learning Engineer to help shape the future of responsible AI evaluation for the next generation of generative features.

In this role, you will work to assess, quantify, and improve the safety and inclusivity of Apple's Generative-AI powered features and products. Your work will 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. You will directly influence how we evaluate, align, and monitor the safety of large language and multimodal models, while upholding Apples values, privacy, and quality standards.

As part of Apple's Responsible AI group within the Software Engineering 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. You'll anticipate safety risks and deliver trusted, high‑quality AI experiences to users around the globe. We are seeking a visionary Senior Machine Learning Engineer to drive Responsible AI Evaluation efforts for global generative AI products. In this role, you will provide critical technical execution for operationalizing policy and risk assessments into measurable criteria; designing datasets; developing LLM- and human-in-the-loop methods for data analysis; and implementing robust data pipelines to produce reliable, scalable insights that inform ship/no-ship product decisions.

Pre- and post-launch, you will be deeply hands-on-analyzing evaluation results, conducting failure investigations, and leveraging human and automated feedback to continuously improve feature safety and build user trust. As a senior technical leader on the team, you will champion technical excellence, empower leadership with data-driven safety recommendations, and systematically solve complex engineering roadblocks. This role heavily draws on applied data science, scientific investigation, cross-functional collaboration, and defending safety metrics to stakeholders and decision-makers.Develop metrics for the evaluation of safety and fairness risks inherent to generative models and Gen-AI features. Design datasets, identify data needs, and implement creative solutions to scale and expand data coverage through human and synthetic generation methods. Develop sampling strategies and combine human annotation with auto-grading to deliver high-quality, high-confidence insights at a fast pace and large scale. Design, implement, and optimize data pipelines, collaborating cross-functionally to execute end-to-end safety evaluations. Drive operational excellence by automating manual workflows and optimizing evaluation velocity to meet rapid product release cycles. Distill complex project findings into actionable insights for product engineering teams and safety policy development. Work with highly-sensitive content, including exposure to offensive and controversial material.Experience working with multimodal models, agentic systems, and/or diverse languages and locales Experience with compliance and regulatory needs in the AI space, specifically regarding child safety, clinical/health applications, or companionship chatbots Experience conducting large scale benchmarking across models and capabilities