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Applied Research Scientist, Proactive Intelligence - Personal and Agentic SearchApple • United States
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Applied Research Scientist, Proactive Intelligence - Personal and Agentic Search

Apple
  • US
    United States
  • US
    United States
Postuler Maintenant

À propos

AI represents a big opportunity to elevate Apple's products and experiences for billions of people globally. We are looking for Applied Research Scientists with a background and interest in Agentic Systems. You will be leveraging state-of-the-art Generative models to ship extraordinary products, services, and customer experiences for the iPhone, Mac, Apple Watch, iPad and more. \\n\\nThe mission of Proactive Intelligence is to improve Apple platforms by better understanding, anticipating and adapting to user behavior by using machine learning to build phenomenal features that are built right into Apple platforms. Our team provides an opportunity to be part of an incredible research and engineering organization within Apple. The ideal candidate will have industry experience across a range of modeling problems relevant to LLM-powered search and agentic systems, including Training and Fine-Tuning Large Language Models (LLMs), Learning from Human Preferences, LLM-based Evaluation and Judging, Retrieval and Planning, and Causal Analysis of Model Failures. \\n\\nWorking knowledge of large-scale data processing especially with structured data, probabilistic modeling and statistics will broaden your role and effectiveness in this position.\\nThis role contributes directly to Personal Search and Agentic Search inside Siri - the capabilities that let users reason over their own data and act on it through natural conversation.\\n
As an Applied Research Scientist on our team, you will design and implement ML algorithms that process data in different Apple products. You will train and fine-tune generative models and agentic systems, design the evaluation methodology and ground-truth surfaces that measure their quality, and build the causal-analysis tooling that explains why agents fail and how to fix them. \n\nWhere necessary, you will integrate ML frameworks into our products and leverage cloud services for scalable training, evaluation, and ablation pipelines across locales. You will communicate advanced ideas to a focused team of researchers in the spirit of developing innovative tools and metrics that change the way we look at problems.\n\n You will work closely with other cross-functional teams to align messaging, contribute to roadmaps and contribute software back into different repos for proper integration with core systems.You will write clean, maintainable and production code with appropriate documentation and tests. You will contribute to architecture decisions, design reviews and peer code reviews!
Strong programming skills in Python and/or C++ with 6+ years of experience in using these languages for machine learning (ML) modeling and applied research\nM.S. or PhD in Computer Science, or a related fields such as Electrical Engineering, Robotics, Statistics, Applied Mathematics or equivalent experience. A minimum of 6 years of experience in applied ML and/or product development.\nFundamental knowledge of ML concepts and hands-on experience in building deep-learning systems\nStrong software engineering skills to create scalable and robust infrastructure for machine-learning data, modeling and evaluation systems\nProven ability to train and debug machine-learning systems: defining metrics and datasets, performing error analysis and training models in a modern ML framework
Familiarity with researching current ML literature and math including optimization methods and modeling techniques\nPassionate about building extraordinary personal and agentic search experiences powered by Generative AI\nCreative, collaborative and project focused with an ability to work hands-on in multi-functional teams\nExperience designing LLM-as-Judge methodologies, ground-truth datasets, and diagnostic tooling for generative systems\nProficiency in using ML toolkits such as PyTorch, TensorFlow, SkLearn etc.
  • United States

Compétences linguistiques

  • English
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