Applied Research Scientist, Proactive Intelligence, — Agentic Systems and Generative Modeling

Apple • Cupertino, CA

12d

About The Position

The Applied Research Scientist will work on Agentic Systems and Generative Modeling within Apple’s Proactive Intelligence team. The team uses machine learning to improve Apple platforms by understanding, anticipating, and adapting to user behavior, building features into Apple products and experiences.

The role involves designing and implementing machine-learning algorithms that process data across Apple products, and training generative AI models and agentic systems using deep reinforcement learning. The scientist may integrate ML/RL frameworks into products, train large-scale agents, and use cloud services for scalable, distributed training and simulation of agent behaviors.

The scientist will communicate research ideas, help develop tools and metrics, collaborate with cross-functional teams on messaging and roadmaps, and contribute software to repositories for integration with core systems. The role also includes writing documented, tested, maintainable production code and contributing to architecture decisions, design reviews, and peer code reviews.

Requirements

• Strong programming skills in Python and/or C++, with at least 3 years of experience using these languages for machine-learning modeling and applied research.
• M.S. or Ph.D. in Computer Science or a related field, such as Electrical Engineering, Robotics, Statistics, or Applied Mathematics, or equivalent experience.
• At least 3 years of experience in applied machine learning and/or product development.
• Fundamental knowledge of machine-learning concepts and hands-on experience building deep-learning systems.
• Strong software-engineering skills for creating scalable, robust infrastructure for machine-learning data, modeling, and evaluation systems.
• Proven ability to train and debug machine-learning systems, including defining metrics and datasets, performing error analysis, and training models in a modern machine-learning framework.

Nice To Haves

• Familiarity with current machine-learning literature, mathematics, optimization methods, and modeling techniques.
• Passion for building autonomous systems with generative AI.
• Creative, collaborative, project-focused approach and ability to work hands-on in multifunctional teams.
• Proficiency with machine-learning toolkits such as PyTorch, TensorFlow, or Scikit-learn.

Responsibilities

• Design and implement machine-learning algorithms that process data in Apple products.
• Train generative AI models and agentic systems using deep reinforcement learning.
• Integrate ML/RL frameworks into products where necessary.
• Train large-scale agents and use cloud services for scalable, distributed training and simulation of agent behaviors.
• Communicate advanced ideas to researchers and contribute to developing innovative tools and metrics.
• Work with cross-functional teams to align messaging and contribute to roadmaps.
• Contribute software to repositories for integration with core systems.
• Write clean, maintainable production code with appropriate documentation and tests.
• Contribute to architecture decisions, design reviews, and peer code reviews.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level