Proactive Intelligence, Applied Research Scientist — Generative AI
Santa Clara Valley (Cupertino), California, United States
Machine Learning and AI
AI represents a huge 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 Generative AI. 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 e.g., Conversational Agents, Sequential Decision Making, Reinforcement Learning, Autonomous Systems, Human Preference Learning and 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.
- Strong programming skills in Python and/or C++ with 5+ years of experience in using these languages for machine learning (ML) modeling and applied research
- Proficiency in using ML toolkits such as PyTorch, TensorFlow, SkLearn etc.
- 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 deep learning data, modeling, and evaluation systems
- Proven ability to train and debug deep learning systems: defining metrics and datasets, performing error analysis and training models in a modern ML framework
- 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
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 agent behaviors using deep reinforcement learning to solve hard problems/tasks. 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.
Education & Experience
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 5 years of experience in applied ML and/or product development.
- Publications in top-tier conferences in a plus e.g., NeurIPS, ICML, ICLR, ICRA etc.
- Hands-on development experience within OSS Libraries and RL environments such as OpenAI Gym, MuJoCo, RLLib, Stable Baselines 3, Apple Core ML etc.
- Experience in applying deep learning to robotics problems and predicting multimodal behaviors for agents viatechniques such as MDP, Monte-Carlo methods, TD learning, policy approximations etc.
- Experience with hardware specific optimization of ML models and deployment
- Experience developing software for mobile devices and heterogenous compute environments (eg. iOS, watchOS)