Proactive Intelligence, Applied Research Scientist — Agentic Systems and Ge at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

25 Dec, 25

Salary

0.0

Posted On

26 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, C++, Machine Learning, Applied Research, Deep Learning, Reinforcement Learning, Generative AI, Probabilistic Modeling, Statistics, Software Engineering, Large Language Models, Data Processing, Sequential Decision Making, Autonomous Systems, Error Analysis, ML Frameworks

Industry

Computers and Electronics Manufacturing

Description

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.

Responsibilities

As an Applied Research Scientist, you will design and implement machine learning algorithms for various Apple products. You will train Generative AI models and Agentic systems using deep reinforcement learning to address complex challenges.