AIML - SW Engineer, Batch processing team
Apple
AIML - SW Engineer, Batch processing team
Santa Clara,California,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 innovative 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 employ 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 $143,100 and $264,200, 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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