AI Research Scientist - Apple, Inc. : Job Details

Cupertino, California, United States

Software and Services

Apple Maps is seeking a passionate AI research scientist to help shape the future of geospatial intelligence and revolutionize how the changing world is understood, modeled and experienced. As part of our AI research team, you will research and apply cutting-edge deep learning and generative AI technologies to create next-generation mapping solutions, solving challenging, real-world problems with massive global impact. This role is pivotal in advancing Apple's geospatial capabilities, enabling smarter, more responsive mapping systems that can adapt to the dynamic nature of the world!

In this role, you'll work on some of the most challenging problems at the intersection of deep learning, computer vision, LLM, Foundation Models, Agentic AI, and geospatial data. You'll collaborate with a cross-functional team of engineers, ML scientists, and map specialists to build AI systems that understand the world at scale. You will:

• Lead and contribute to applied research projects that push the boundaries of AI applied to geospatial intelligence.
• Design and develop advanced machine learning and deep learning models to understand large scale complex geospatial data and perform geospatial reasoning.
• Experiment with intelligence systems capable of interpreting and updating maps autonomously.
• Collaborate with engineering and map specialists to translate prototypes into scalable systems with highly user-centric UI implementations.
• Stay on top of the latest advancements in AI/ML and contribute to our technical vision and strategy.
• Advocate for responsible AI practices ensuring ethical solutions in alignment.

• MS with comparable industry experience in computer science, Artificial Intelligence, Machine Learning or related field.
• Strong theoretical and practical background in machine learning, deep learning, and computer vision.
• Proven experience in developing, fine-tuning and deploying LLMs, VLMs, or other Generative AI models.
• Proficiency in Python and deep learning frameworks like PyTorch, TensorFlow, or JAX.
• Demonstrated problem solving skills to translate complex real-world problems into machine learning tasks and develop practical, scalable solutions.
• Strong interpersonal collaboration and communication skills.

• PhD in computer science, Artificial Intelligence, Machine Learning or related field.
• Track record of patents, or publications in top AI/ML or GIS conferences or journals.
• Hands-on experience with processing large datasets, training ML models in distributed environments, and deploying large-scale models in production.
• Familiarity with emerging technologies such as Mixture of Experts (MoE) architectures, AI agents, and Retrieval-Augmented Generation (RAG).
• Understanding of post-training strategies like RLHF, DPO, or equivalent approaches.

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 $147,400 and $272,100, 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.

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.