AIML - Machine Learning Engineer, Machine Learning ...

AIML - Machine Learning Engineer, Machine Learning Platform & Infrastructure 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 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 scale of Apple. Description We design, build and maintain infrastructure to support features that empower billions of Apple users. Our team processes billions of requests every day across our search and foundation model platform. We take full end-to-end ownership of our services, driving them through every stage meticulously, encompassing conception, design, implementation, deployment, and maintenance. As a result, each one of us takes our responsibilities seriously. In this team, you'll have the opportunity to work on incredibly complex large scale systems with trillions of records and petabytes of data, work along side Foundation Model Research team to optimize inference for cutting edge model architectures, and work closely with product teams to build production grade solutions for millions of customers in real time. Minimum Qualifications Strong background in computer science: algorithms, data structures and system design 10+ year experience on large scale distributed system design, operation and optimization Familiar with one of the popular ML Frameworks like Pytorch, Tensorflow Excellent interpersonal skills able to work independently as well as cross-functionally Key Qualifications Preferred Qualifications Proficient in building and maintaining systems written in modern languages (e.g. Golang, Python) Familiar with fundamental Deep Learning architectures such as Transformers, Encoder/Decoder models. Familiarity with Nvidia TensorRT-LLM, vLLLM, DeepSpeed, Nvidia Triton Server etc. Experience writing custom CUDA kernels using CUDA or OpenAI Triton. 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 $197,400 and $360,200, and your base pay will depend on your skills, qualifications, experience, and 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 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 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. ( Apple Footer 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 (Opens in a new window) . Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) . Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you're applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines (opens in a new window) applicable in your area. Apple participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program (Opens in a new window) . Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) . Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .

Created: 2024-11-05