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

What you'll do

• Design and implement machine learning algorithms to process data across various Apple products.
• Train Generative AI models and Agentic systems using deep reinforcement learning to solve complex problems.
• Integrate ML/RL frameworks into products to train large-scale agents.
• Utilize cloud services to enable scalable and distributed training and simulation of agent behaviors.
• Develop innovative tools and metrics to evaluate and improve machine learning research.
• Write clean, maintainable, and production-ready code with appropriate documentation and tests.
• Contribute to architecture decisions, design reviews, and peer code reviews.

What we're looking for

• MS or PhD in Computer Science, Electrical Engineering, Robotics, Statistics, Applied Mathematics, or equivalent experience.
• At least 3 years of experience in applied machine learning and/or product development.
• 3+ years of experience using Python and/or C++ for machine learning modeling and applied research.
• Fundamental knowledge of ML concepts and hands-on experience building deep-learning systems.
• Strong software engineering skills to create scalable infrastructure for ML data, modeling, and evaluation.
• Proven ability to train and debug machine-learning systems including defining metrics, datasets, and performing error analysis.
• Proficiency in using ML toolkits such as PyTorch, TensorFlow, and SkLearn.
• Familiarity with current ML literature, optimization methods, and modeling techniques.