Applied Research Scientist, Proactive Intelligence, — Agentic Systems and Generative Modeling
Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Mar 11, 2026. Apple scores B on the Alion truth index.
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. The 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 for this role will have industry experience working on a range of modeling problems, including Sequential Decision Making, Reinforcement Learning, Autonomous Systems, Learning from Human Preferences and Training Large Language Models (LLMs). Working knowledge of large-scale data processing especially with structured data, probabilistic modeling and statistics will broaden your role and effectiveness in this position.
Description
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 Generative AI models and Agentic systems using deep reinforcement learning to solve hard problems. Where necessary, you will also work on integrating ML/RL frameworks into our products to train large-scale agents and leverage cloud services to enable scalable and distributed training/simulation of agent behaviors. 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. 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!
Minimum Qualifications
Strong programming skills in Python and/or C++ with 3+ years of experience in using these languages for machine learning (ML) modeling and applied research
M.S. or PhD in Computer Science, or a related fields such as Electrical Engineering, Robotics, Statistics, Applied Mathematics or equivalent experience. A minimum of 3 years of experience in applied ML and/or product development.
Fundamental knowledge of ML concepts and hands-on experience in building deep-learning systems
Strong software engineering skills to create scalable and robust infrastructure for machine-learning data, modeling and evaluation systems
Proven ability to train and debug machine-learning systems: defining metrics and datasets, performing error analysis and training models in a modern ML framework
Preferred Qualifications
Familiarity with researching current ML literature and math including optimization methods and modeling techniques
Passionate about building extraordinary autonomous systems with Generative AI
Creative, collaborative and project focused with an ability to work hands-on in multi-functional teams
Proficiency in using ML toolkits such as PyTorch, TensorFlow, SkLearn etc.