Job Information
Apple AIML - ML Engineer, Batch processing team in Seattle, Washington
AIML - ML Engineer, Batch processing team
Seattle,Washington,United States
Machine Learning and AI
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 ever smarter for our users? The Foundation Model Batch Inference team are building groundbreaking technology for large scale inference of foundation models, including state-of-the-art large language models (LLMs) and multimodal models. Our batch inference platform powers billions of foundation model inference queries across a variety of Apple products. As part of this group, you will work with one of the most exciting high performance computing environments for foundation models inference, with petabytes of data and billions of queries, and have an opportunity to imagine and build products that delight our customers every single day.
Description
We design and build infrastructures to support features that empower billions of Apple users through advanced intelligence systems. Our team processes trillions of links to find the best content to surface to users via search and other intelligent features. We also analyze pages to extract critical features for indexing, ranking, and retrieval. Join us and: * build and optimize large scale batch inference solutions * build scalable and efficient system to fully utilize diverse high performance GPU fleet
Minimum Qualifications
Strong coding skills
Strong background in computer science: algorithms and data structures
Strong experience with Docker containerization and Kubernetes orchestration, familiar with AWS EKS, Amazon S3 or GCP
Extensive expertise in designing robust, large scale backend system, taking into account for performance, scalability, security and maintainability.
Excellent interpersonal skills able to work independently as well as in a team
Key Qualifications
Preferred Qualifications
Familiar with one of the popular ML Frameworks like PyTorch, Tensorflow
Familiar with foundation model architectures such as Transformers, Encoder/Decoder
Familiar with fundamental model inference
Familiar with MapReduce style batch jobs
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 $135,400 and $250,600, 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 (https://www.apple.com/careers/us/benefits.html) 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 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. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf)
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