Sr. ML Engineer, Siri User Experience Metrics and Data

We're looking for a Senior Machine Learning Engineer to help build the next generation of tools and platforms that power high-impact decisions across Siri. In this role, you'll operate at the intersection of engineering excellence and business impact. You'll design and implement scalable, reliable systems to transform raw data into actionable insights for leadership. This is a high-visibility, high-impact position with the opportunity to influence the direction of products and strategy\\n\\nThe Siri User Experience Metrics team is at the heart of shaping how users interact with Siri every day. We use data, metrics and insights to continuously improve Siri's User Experience across Apple platforms including iOS, macOS, visionOS, tvOS and watchOS.\\n\\nOur team defines and owns the most critical user facing metrics, builds scalable reporting tools and delivers actionable insights that directly inform product decisions. We collaborate closely with product, platform and feature teams to ensure Siri not only works - but delivers exceptional User Experience. From response time to failure tracking, we make sure Siri feels fast, natural and helpful wherever users need it.\\n\\nAs a Senior ML engineer on the Siri User Experience Metrics team, you will have significant influence and responsibility in improving Siri user experience by contributing to efforts including building a trustworthy and explainable anomaly detection system to automatically identify regressions in Siri performance and alert engineering teams with actionable insights for debugging performance issues. \\n\\nIf this sounds like you, you're someone who's laser-focused on impact - bringing sharp programming skills, strong problem-solving abilities and clear communication to the table, all driven by a passion for building exceptional products.\\n\\nYou'll have the opportunity to drive meaningful impact across all Apple platforms by collaborating closely with Engineering, Product, Testing and Quality teams. Your work will directly enhance the Siri experience for billions of users - shaping how people interact with Apple every day.

We're looking for a Senior Machine Learning engineer with a proven record of building scalable statistical systems for business applications in a fast-paced environment. In this role you will drive the technical vision for Siri's automated anomaly detection platform for detecting performance and reliability regressions. \n\nYou are someone who is passionate about shipping quality code and continually improving our anomaly detection systems. You will be responsible for defining, developing and delivering key features for high quality alerting to enable teams to troubleshoot regressions rapidly.\n\nYou are someone who works extremely well across teams and organizations and demonstrates strong communication and technical leadership skills and the ability to engage with colleagues and leadership to find common ground on solving hard problems. You are someone who shares technical vision to leadership and engineering teams, gathers feature requirements, defines technical roadmaps and executes efficiently.\n\nYou will be responsible for technically representing the team and communicating progress on key deliverables across the organization from peer groups to senior leadership. As the Senior ML engineer on the team, you will be responsible for owning the technical roadmap, onboarding and mentoring team members, and leading the team to deliver high-impact outcomes.\n\nYou are someone comfortable executing in a rapidly changing environment with ambiguous requirements to drive impact incrementally. You demonstrate strong problem solving skills and are self-directed with a proven ability to execute. You continually desire learning and demonstrate attention to details and find opportunities to innovate and share knowledge with others.

Master's degree with 8+ years of industry experience in machine learning, or Ph.D. with 5+ years, applying ML to real-world business problems.\nStrong understanding of core ML concepts, with particular depth in unsupervised learning methods (clustering, dimensionality reduction, density estimation), and a solid foundation in feature engineering, model evaluation, regularization, and optimization.\nAdvanced coding skills in Python (5+ years) with pandas, scikit-learn, and at least one deep learning framework (PyTorch or TensorFlow).\nHands-on experience data preprocessing, building and training ML models using distributed processing frameworks such as PySpark, Spark, or Flink. \nExperience applying large language models (LLMs) for downstream tasks (classification, labeling, enrichment), with the ability to perform fine-tuning or parameter-efficient adaptation (e.g., LoRA). Must be capable of deploying and optimizing models in on-premise, server, or on-device environments, rather than relying solely on hosted third-party APIs\nDemonstrated ability to set technical vision, lead complex projects, and drive impact in cross-functional environments, with strong communication and problem-solving skills.

Proven expertise with anomaly detection and time series modeling (e.g., Isolation Forest, autoencoders, ARIMA, LSTM) and experience building production frameworks supporting multiple engineering and product teams.\nExperience with LLM workflows (domain adaptation, RAG) and deploying optimized ML/LLM models on mobile or server environments (e.g., Core ML, TensorFlow Lite, ONNX Runtime) for performance, cost, and privacy.\nExperience in developing ML infrastructure, and large-scale operations, including model serving, distributed training, CI/CD for ML pipelines, and platform monitoring across millions of devices or events.\nFamiliarity with composite metrics and interpretability tools (e.g., SHAP, LIME), with a track record of publications, patents, or open-source contributions in ML/LLMs, anomaly detection, or time series modeling.