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Selected role

Senior Machine Learning Engineer, Machine Learning Platform Technologies

Apple San Francisco Bay Area, CA, US

$171k - $302k Senior Full-time

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.

At Apple, imagination and ambition come together to shape what’s next. Every product we build, every service we design, and every experience we deliver is born from collaboration-making each other’s ideas stronger and more impactful. We believe in thinking differently, challenging the status quo, and pushing the boundaries of technology and intelligence to create products that bring joy and change lives for the better. Our strength comes from the diversity of our people and perspectives, and when everyone is included, we do the best work of our lives. If you’re bold, curious, and passionate about building best-in-class technology, Apple is the place to not just join something-but to add something.

As part of this group, you will develop GenAI search and recommendation application end to end and partner with a lot of engineering teams across Apple.

Description

The Partner Adoption team, part of the Machine Learning Platform Technologies organization, is the backbone of onboarding applications to Apple’s world-class search and recommendation platform. In this role, you’ll work end-to-end on feature and product design across a broad range of Apple services-including Apple Music, TV+, App Store, Books, Games, Podcasts, Siri, and more. As a key member of the team, you’ll design and build large-scale server-side functionality while also exploring and delivering cutting-edge GenAI applications and features powered by large language models. You’ll partner closely with product, platform, and design teams to bring innovations to life-reaching millions, and even billions, of users worldwide with the reliability and excellence Apple is known for.

Preferred Qualifications

Familiar with GenAI Applications and popular agentic framework like Langchain and Langgraph

Familiar with embedding model and llm serving like Nvidia TensorRT-LLM, vLLLM, DeepSpeed, Nvidia Triton Server etc.

Familiar with very large scale serving system

Minimum Qualifications

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

5 year+ industry experience in distributed system and ML Modeling (Search, Recommendation, NLP, Ads, Statistics).

Experience with high throughput services particularly at supercomputing scale.

Proficient with running applications on Cloud (AWS / Azure or equivalent) using Kubernetes, Docker etc.

Proficient in building and maintaining systems written in modern languages (eg: Golang, Rust, Python)

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 $171,600 and $302,200, 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 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.

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