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Apple

Machine Learning Engineer, Foundation Model Services

Santa Clara, CA$175,000 – $308,500Posted 24 days ago

Apply on company site View full job

Why you should apply for a job to Apple:

Ranked as one of the Best Technology Companies in 2020
3.7/5 in overall job satisfaction
3.1/5 in supportive management
66% say women are treated fairly and equally to men
65% would recommend this company to other women
66% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

Do you think differently? Are you eager to break the status quo, bold and ambitious, unafraid to take risks, and passionate about building best-in-class technology? If so, there's no better place to do it than Apple. The Foundation Model Services team builds the frameworks, services, and tools that run Apple's largest foundation models in production. Our infrastructure powers intelligent experiences across products people use every day - Search, Music, TV, the App Store, Messages, Photos, Spotlight, Safari, Siri, and more - serving millions of queries at incredibly low latency while drawing every ounce of performance from our hardware. Join us and you'll help bring intelligence to billions of users around the world, working on optimizing and serving large language, vision, and speech models at Apple's scale.

Description

Work closely with product teams to build production-grade solutions that launch models serving customers in real time.

Partner with foundation model researchers to prototype and develop inference for cutting-edge model architectures, and build tools that help us understand and remove performance bottlenecks across different hardware and use cases.

Write high-quality code, learn quickly in a fast-moving field, and grow your impact as you take on larger pieces of the system.

Preferred Qualifications

Familiarity with Nvidia TensorRT-LLM, vLLLM, DeepSpeed, Nvidia Triton Server etc.

Minimum Qualifications

2+ years of industry experience building and shipping production software and/or machine learning systems.

Proficiency in a modern programming language such as Go or Python.

Experience deploying and operating services on a cloud platform (AWS, Azure, GCP, or equivalent) using containers and Kubernetes/Docker.

5 year+ industry experience in ML technologies (LLMs, Machine Learning, NLP, Information Retrieval, Statistics).

Experience building or operating high-throughput, low-latency services.

Strong communication and collaboration skills, with the ability to partner across research and product teams.

Bachelor's degree or higher in Computer Science or related technical field.

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 $175,000 and $308,500, 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 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.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology: Manufacturing

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