Machine Learning Engineer - Multimodal Intelligence

Imagine what you could do here. At Apple, new ideas have a way of becoming

extraordinary products, services, and customer experiences very quickly. Bring

passion and dedication to your job and there's no telling what you could

accomplish. Multifaceted, amazing people and inspiring, innovative technologies

are the norm here. The people who work here have reinvented entire industries

with all Apple Hardware products. The same passion for innovation that goes into

our products also applies to our practices, strengthening our commitment to

leave the world better than we found it. Join us in this truly exciting era of

Artificial Intelligence to help deliver the next groundbreaking Apple products

and experiences! The Multimodal Intelligence team builds and ships the Computer

Vision and Machine Learning systems behind Apple Intelligence — spanning data

collection and curation, training and fine-tuning, evaluation, optimization, and

on-device deployment. Our team has an established track record of delivering

features that combine Apple's sensing hardware with large foundation models,

including Visual Intelligence and the on-device foundation models that power

text and visual understanding across iPhone, iPad, Mac, and Apple Vision Pro. We

are focused on building experiences where a device can see, read, and reason

about the world around it — privately, responsively, and on-device wherever

possible.

DESCRIPTION

We are looking for a Machine Learning Engineer to build the pipelines,

infrastructure, and production systems that turn multimodal foundation models

into shipping Apple Intelligence features. You will own end-to-end model

delivery: building and scaling data curation and training pipelines, fine-tuning

and optimizing large multimodal models for on-device and hybrid execution,

standing up reproducible evaluation and regression testing for text and visual

understanding, and hardening promising approaches into robust, maintainable

production systems under real latency, memory, power, and privacy constraints.

You will work closely with modeling, platform, hardware, and product engineering

teams across Apple — taking future hardware design and product needs into

account as you make implementation decisions — and you will have the opportunity

to collaborate broadly to deliver the best possible products.

MINIMUM QUALIFICATIONS

Experience in deep learning with demonstrated work in at least one area of

multimodal systems (e.g., vision, language, video, audio, etc.) Proficiency in

Python and in a modern deep learning framework such as PyTorch or JAX Experience

with rapid prototyping, reproduction, and validation of research ideas Ability

to work in a collaborative environment Ability to communicate the results of

analyses in a clear and effective manner BS and a minimum of 3 years of relevant

industry experience

PREFERRED QUALIFICATIONS

Master's or PhD, or equivalent practical experience, in Computer Science,

Computer Vision, Machine Learning, or related technical field Deep expertise in

multimodal foundation models, with a focus on practical applications Track

record of translating research into practical applications either through

published work or industry experience Strong applied research experience in at

least one major area of model development (data curation, pre-training,

fine-tuning, alignment, or evaluation), particularly as it applies to multimodal

systems Experience with large-scale training pipelines, including working with

large datasets and scaling models across distributed systems Experience bridging

research ideas with production constraints