AI ML Research Scientist - Foundation Models & Multimodal Intelligence

AIToolboard; United States; On-site; USD 139,500 - 258,100; Full time

Benefits offered by this job

Apple employee stock programs

Discretionary RSU awards

Relocation assistance

Education expense reimbursement

Comprehensive medical and dental

Job summary

Apple Washington, US is seeking a highly skilled engineer to advance foundation models and agentic systems within the Multimodal Intelligence Team (MINT). You will tackle scaling, optimization, and integration challenges for models used across Apple products, aiming to deliver real-world AI experiences with privacy and efficiency.

You will stay current with research, develop data pipelines, and collaborate with engineers to deploy models from lab to production while aligning with Apple standards.

Qualifications

• BS and a minimum of 3 years relevant industry experience.
• Proficiency in Python and at least one modern deep learning framework (PyTorch, JAX, or TensorFlow).
• Experience with large-scale training pipelines and distributed systems.

Responsibilities

• Research, design, and optimize foundation models for real-world Apple products.
• Improve alignment, reasoning, and adaptation of large models for production deployment.
• Design and optimize large-scale data pipelines for robust training and evaluation.
• Collaborate with cross-functional teams to integrate models into software and devices.

Skills

Python

Deep learning

PyTorch

JAX

TensorFlow

Distributed systems

Education

BS in Computer Science or related field

PhD in Computer Science / ML (preferred)

Tools

PyTorch

JAX

TensorFlow

Job description

Apple Washington, US

Full-time

About the Role

Imagine building the next generation of AI-powered experiences at Apple. We are advancing the state of the art in foundation models, applying them across language, vision, and multimodal understanding to power features used by millions of people worldwide. As part of the Multimodal Intelligence Team (MINT), with a track record of delivering innovations from the Apple Foundation Model to real-world applications like Visual Intelligence, you will tackle the practical challenges of scaling, optimizing, for building large models as well as integrating such models and agents into Apple products. You'll collaborate with world-class engineers and scientists to push the boundaries of foundation models and agentic system while delivering real-world impact. Description You will work on advancing the capabilities of foundation models and steering them toward real-world applications in Apple products. This includes researching and developing methods to improve alignment, reasoning, and adaptation of large models to practical use cases, while ensuring they meet Apple's standards for efficiency, scalability, and privacy. A key part of your role will be to stay current with emerging research and identify techniques suitable for real-world deployment, bridging the gap between state-of-the-art advancements and production-ready solutions. You will design and optimize large-scale data pipelines to enable robust training and fine-grained evaluation of foundation models, working with massive multimodal datasets to push the limits of performance. You will explore new ways to enhance reasoning and multimodal understanding, adapting models for Apple's unique ecosystem, from cloud-scale infrastructure to on-device intelligence. Collaboration will be central to your work-you will partner with cross-functional teams of engineers and researchers bring these models to life, ensuring seamless integration into Apple products and creating intelligent natural user experiences.

Minimum Qualifications

• BS and a minimum of 3 years relevant industry experience.


• Proficient programming skills in Python and experience with at least one modern deep learning framework (PyTorch, JAX, or TensorFlow).


• Experience working with large-scale training pipelines and distributed systems.

Preferred Qualifications

• PhD, or equivalent practical experience, in Computer Science, Machine Learning, or a related technical field.


• Demonstrated expertise in deep learning, with either: A publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, COLM, etc), or a strong track record of applying deep learning techniques to real-world products.


• Experience with foundation models (language, vision-language, or multimodal).


• Familiarity with large-scale data pipelines, including data curation, preprocessing, and efficient storage.


• Experience fine-tuning or optimizing large models for production deployment.


• Knowledge of retrieval-augmented generation (RAG), personalization, or grounding techniques.


• Familiarity with privacy-preserving or on-device machine learning.


• Ability to work effectively in a cross-functional, collaborative environment.

Pay & Benefits

• Base pay range for this role is between $139,500 and $258,100, 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.


• Learn more about Apple Benefits.


• Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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.