> Markdown version of [/jobs/ext/4508962-aiml-machine-learning-engineer-evaluation-responsible-ai-and-safety](https://www.wearedevelopers.com/jobs/ext/4508962-aiml-machine-learning-engineer-evaluation-responsible-ai-and-safety). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AIML - Machine Learning Engineer, Evaluation - Responsible AI and Safety - **Company:** Apple Inc. - **Location:** Cupertino, CA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Cognitive Science, Computer Programming, Human-Computer Interaction, Python (Programming Language), Machine Learning, Chatbots, Large Language Models, Pandas, Information Technology, Artificial Intelligence Markup Language (AIML), Data Pipelines - **Published:** November 2, 2026 - **Apply:** https://www.dice.com/job-detail/98b0d176-4d05-4d06-a474-6979c48a14f8 ## About the Role 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 Experience gathering and analyzing varied language, image, voice, video, and/or multi-modal data, including human- and LLM-generated data Experience with LLM-Judges as well as human-in-the-loop techniques, including designing human annotation projects, writing guidelines, and dealing with highly multi-labeled, nuanced, and often conflicting data Proficiency in data science, machine learning, analytics, programming with Python & Pandas, and AI-assisted coding tools; experience with one or more plotting & visualization libraries Cross-functional collaboration skills to prioritize competing projects needs, set and maintain schedules for project milestones, and communicate with all levels of team members, as well as internal and external stakeholders A rigorous approach to metric development; interpretation of experiments and evaluations; and presentation to executives Comfortable leading a team that works with sensitive or potentially offensive content. Preferred Qualifications Experience working in the Responsible AI space Passion for building innovative, high-impact products and teams that draw upon interdisciplinary skills Curiosity about fairness and bias in generative AI systems, and a strong desire to help make the technology more equitable A Social Science or Humanities background, or other demonstrable interest in socio-technical issues Prior scientific research and publication experience Proven track record of contributing to diverse teams in a collaborative environment 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 ## Description 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.