Description
Summary
Do you want to make Siri and Apple products safer for our users? The Siri and Information Intelligence team
is redefining how hundreds of millions of people use their devices to get information. We are an Applied ML team pushing the limits on realtime augmented information retrieval and generation, information safety and search technologies, while also responsible for a few user facing production services. We are part of a wider effort to power information across a variety of Apple products – including Siri, Spotlight, Safari, Messages, Lookup, and more. We are deeply committed to ensuring that our platform remains a safe, welcoming, and trustworthy environment for everyone.
Description
We are looking for a highly skilled Machine Learning Engineer to join our Search Safety team. In this role, you will build and deploy state-of-the-art machine learning models designed to detect, demote, and filter harmful, abusive, or policy-violating content across our search ecosystem. You will work at the intersection of Search, Natural Language Processing (NLP), Image and Trust & Safety, addressing complex challenges like query intent understanding, adversarial evasion, jailbreaking, and multimodal content filtering. If you are passionate about protecting users and building robust ML systems at scale, we want you on our team.
Minimum Qualifications
3+ years of industry related experience, working in collaborative environments
Experience with utilizing PyTorch, TensorFlow, or JAX for training and deploying deep learning models
Understanding product requirements then translating them into modeling tasks and engineering tasks
Proficient in at least two programing languages such as: Python, Go, Java, C/C++
BS in Computer Science, Artificial Intelligence, Machine Learning, Safety, Computer Vision or related field or equivalent work experience
Preferred Qualifications
Experience working on content moderation, spam detection, fraud, or Trust & Safety ML teams.
Experience in red-teaming, adversarial training, or robustness evaluation of ML models.
Building machine-learned models and integrating safety signals directly into the search ranking and retrieval pipelines, balancing safety constraints with search relevance and user engagement.
MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Safety, Computer Vision or related fieldor equivalent work experience
Apple