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

3 days ago Cupertino, CA

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!

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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.

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

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .

Client-provided location(s): Cupertino, CA
Job ID: apple-200623064-0836_rxr-658
Employment Type: OTHER
Posted: 2025-11-10T19:06:40

Perks and Benefits

  • Health and Wellness

    • Parental Benefits

      • Work Flexibility

        • Office Life and Perks

          • Vacation and Time Off

            • Financial and Retirement

              • Professional Development

                • Diversity and Inclusion

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