招聘
Imagine being at the forefront of an evolution where cutting-edge AI meets the elegance of Apple silicon. The On-Device Machine Learning team transforms groundbreaking research into practical applications, enabling billions of Apple devices to run powerful AI models locally, privately, and efficiently. We stand at the unique intersection of research, software engineering, hardware engineering, and product development, making Apple the leading destination for machine learning innovation.
Our team builds the essential infrastructure that enables machine learning at scale on Apple devices. This involves onboarding cutting-edge architectures to embedded systems, developing optimization toolkits for model compression and acceleration, building ML compilers and runtimes for efficient execution, and creating comprehensive benchmarking and debugging toolchains. This infrastructure forms the backbone of Apple's machine learning workflows across Camera, Siri, Health, Vision, and other core experiences, contributing to the overall Apple Intelligence ecosystem.
If you are passionate about the technical challenges of running sophisticated ML models across all devices, from resource-constrained devices to powerful clusters, and eager to directly impact how machine learning operates across the Apple ecosystem, this role presents an exciting opportunity to work on the next generation of intelligent experiences on Apple platforms.
Description:
We are seeking an ML Integration Engineer. In this role, you will ensure Apple's inference stack allows integrating ML workflows end-to-end with excellent user experience, flawless functionality, and maximum performance. This role is far reaching and you will partner with teams across our ML deployment stack, from ML model developers to runtime engineers, as you ensure the best experience, functionality, and maximum performance for ML workflows. The scope of work is wide, spanning model-side updates, ML frameworks export, custom kernels, compiler optimization, and development of analysis and debugging tools.
As a power user of Apple's ML infrastructure, you will also help spearhead the integration of the latest and most capable models with strong, competitive performance across hardware targets, showcasing the practical power of Apple's authoring and runtime APIs. This role offers the unique opportunity to shape how ML developers experience Apple's end-to-end inference stack, from model creation to deployment.","responsibilities":"Ensure functional and performant integration of Apple's ML models across the inference stack.
Integrate Apple's ML tools into internal and external model repositories to demonstrate and stress-test model ingestion with peak efficiency and performance.
Develop optimizations across the pipeline, including model-level transformations, custom operations, or compiler optimizations to improve inference efficiency.
Spearhead the integration of the cutting-edge ML models with peak performance, using these examples to validate or improve Apple's inference stack.
Preferred Qualifications:
Experience with C++, Swift.
Experience with GPU kernel optimizations.
Experience with MLIR/LLVM or similar compiler toolchains.
Familiarity with Hugging Face or other model repositories.
Minimum Qualifications:
Bachelors in Computer Sciences, Engineering, or related discipline.
Proficient in Python programming. Some familiarity with C++ is required.
Proficiency in at least one ML authoring framework, such as Py Torch, MLX, and JAX.
Understanding of ML fundamentals, including common architectures such as Transformers.
Understanding of GPU programming paradigms.
Strong communication skills, including ability to communicate with cross-functional audiences.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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 .
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 $181,100 and $318,400, 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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About Apple

Apple
PublicA technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.
10,001+
Employees
Cupertino
Headquarters
$3.5T
Valuation
Reviews
4.0
10 reviews
Work Life Balance
4.0
Compensation
4.2
Culture
3.8
Career
3.5
Management
3.2
75%
Recommend to a Friend
Pros
Great coworkers and people
Excellent benefits and perks
Fast-paced and engaging work environment
Cons
High expectations and pressure
Management quality varies
Limited career progression opportunities
Salary Ranges
17,968 data points
L2
L3
L4
L5
L6
L2 · Business Analyst L2
0 reports
$114,215
total / year
Base
$45,686
Stock
$57,108
Bonus
$11,422
$79,951
$148,480
Interview Experience
5 interviews
Difficulty
3.4
/ 5
Duration
28-42 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 40%
Negative 40%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Onsite/Virtual Interviews
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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