Proactive Intelligence, Applied Research Scientist — Generative AI

Proactive Intelligence, Applied Research Scientist — Generative AI 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! 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 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. Minimum Qualifications M.S. or PhD in Computer Science, or a related field 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. 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. Key Qualifications 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. Publications in top-tier conferences are 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 via techniques 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 heterogeneous compute environments (e.g., iOS, watchOS). Education & Experience Additional Requirements Pay & Benefits At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $143,100 and $264,200, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.

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