AIML - Machine Learning Engineer, Evaluation - Responsible AI and Safety
Engineering-manager role leading Apple's Responsible AI evaluation team: assessing and improving the safety and inclusivity of generative AI features (LLM text, diffusion image, multimodal) via LLM-judge and human-in-the-loop pipelines, dataset design, and metrics built with Python/Pandas to inform ship/no-ship decisions.
- Compensation
- Not disclosed
- Location
- Cupertino
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- MS/PhD in CS, Linguistics, Cognitive Science, HCI, Psychology, Mathematics, Physics, or similar field + 4 years relevant experience, or BA/BS with 8+ years
- 2+ years directly managing engineering teams
- Experience gathering and analyzing language, image, voice, video, and/or multimodal data, including human- and LLM-generated data
- Experience with LLM-Judges and human-in-the-loop techniques, including designing human annotation projects and writing guidelines
- Proficiency in data science, machine learning, analytics, Python & Pandas, and AI-assisted coding tools
- Experience with plotting & visualization libraries
- Cross-functional collaboration skills to prioritize competing needs, set schedules, and communicate with stakeholders
- Rigorous approach to metric development, interpretation of experiments/evaluations, and presentation to executives
- Comfortable leading a team working with sensitive or potentially offensive content
Nice to have
- Experience working in the Responsible AI space
- Curiosity about fairness and bias in generative AI systems
- Social Science or Humanities background, or interest in socio-technical issues
- Prior scientific research and publication experience
- Proven track record of contributing to diverse teams
- Experience with multimodal models, agentic systems, and/or diverse languages and locales
- Experience with AI compliance/regulatory needs (child safety, clinical/health, companionship chatbots)
- Experience conducting large-scale benchmarking across models and capabilities
Full description
Join Us in Shaping the Future of Generative AI at Apple!
Are you passionate about building and leading teams that make AI systems safer, more inclusive, and globally representative? Apple is seeking an experienced Engineering Manager to lead a team shaping the future of responsible AI evaluation for the next generation of generative features.
In this role, you will lead a team of machine learning engineers and data scientists working to assess, quantify, and improve the safety and inclusivity of Apple’s Generative-AI powered features and products. You and your team's 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 Apple's 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 set technical direction, anticipate safety risks, and develop a team to deliver trusted, high‑quality AI experiences to users around the globe.
We are seeking a visionary Machine Learning Engineering Leader to build, mentor, and develop a high-performing team, driving Responsible AI Evaluation efforts for global generative AI products. In this role, you will provide critical technical direction for operationalizing policy and risk assessments into measurable criteria; designing datasets; developing LLM- and human-in-the-loop methods for data analysis; and overseeing the implementation of data pipelines to produce reliable, scalable insights to inform ship/no-ship product decisions. Pre and Post-launch, you will remain 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 champion for your team, you will foster an inclusive culture of technical excellence, empower senior leadership with safety recommendations, and systematically remove roadblocks to ensure team success. This role heavily draws on applied data science, scientific investigation and interpretation, strategic cross-functional stakeholder management, including negotiating requirements and defending safety metrics to leadership, and metrics reporting and presentation to stakeholders & decision-makers.
Minimum Qualifications
- MS or PhD in Computer Science, Linguistics, Cognitive Science, HCI, Psychology, Mathematics, Physics, or a similar science or technology field with a strong basis in scientific data collection and analysis + at least 4 years of relevant work experience, or BA/BS with 8+ years of relevant work experience, with 2+ years directly managing engineering teams