AIML- Machine Learning Engineer, Machine Learning Platform Technologies

Role Number : 200607382-3401

Summary

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish.

Do you want to make Siri and Apple products more intelligent for our users? The Information Intelligence Infrastructure team is building groundbreaking technology for search, natural language processing, artificial intelligence and machine learning. Our infrastructure is the back-bone of Apple Intelligence. It powers the largest Apple foundation models on servers and a wide gamut of services at Apple including Apple Search, Apple Music, AppleTV, AppStore, iMessages, Photos & Camera, Spotlight, Safari, Siri and upcoming ever exciting Apple products serving millions of queries every day with incredible low latencies, drawing every ounce of compute from our hardware.

As part of this group, you will work with one of the most exciting high performance computing environments, with petabytes of data, millions of queries per second, and have an opportunity to imagine and build products that delight our customers every single day. You will have a chance to work on optimizing billions of parameter language and vision and speech models using state of the art technologies and make it run at the scale of Apple.

Description

Join our dynamic team at Apple, where we design, build, and maintain large-scale infrastructure supporting search and AI features for billions of users globally.

In this team, you will have the opportunity to work on large-scale, complex systems that process trillions of records and petabytes of data. You will design and implement scalable data mining information extraction algorithms and machine learning / deep learning models, work alongside Foundation Model Research teams to curate high-quality datasets for cutting-edge model architectures, and partner closely with product teams to build production-grade solutions for millions of customers in real time.

We value end-to-end ownership and meticulous attention to detail, providing an environment where you can tackle complex challenges at an unparalleled scale. Your responsibilities will span the full service lifecycle, from conception and design to deployment and maintenance, offering a unique opportunity to influence Apple's AI-driven future.

Minimum Qualifications

Master's degree or Ph.D. in Computer Science, Machine Learning, or related field, or equivalent experience

Strong experience in developing and evaluating scalable ML / DL features, demonstrating a passion for understanding and improving model / data quality

Strong programming skills and hands-on experience using one of the deep learning frameworks : PyTorch, Tensorflow or Jax.

2+ years of experience or equivalent in large-scale data processing using programming language Java, Scala or Python.

Excellent interpersonal skills able to work independently and in close partnership with ML researchers

Preferred Qualifications

The ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively with multi-functional teams.

Experience managing rapid prototyping and proof-of-concept development in ML / AI

Familiar with challenges associated with training large models and working with large data

Understanding of ML operations, including model development, evaluation, and deployment

Familiar with fundamental Deep Learning architectures such as Transformers, Encoder / Decoder models.

Familiar with Nvidia TensorRT-LLM, vLLLM, Nvidia Triton Server etc.

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. Learn more about your EEO rights as an applicant () .