招聘

On-Device ML Infrastructure Engineer (ML Insights and Forecasting)
Seattle, WA
·
On-site
·
Full-time
·
2w ago
Compensation
$139,500 - $258,100
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Healthcare
•401k
•Equity
•Learning
Required Skills
Python
Machine Learning
ML frameworks
Software design
The On-Device Machine Learning team at Apple is responsible for enabling the Research to Production lifecycle of innovative machine learning models that power magical user experiences on Apple's hardware and software platforms. Apple is the best place to do on-device machine learning, and this team sits at the heart of that area, working with research, SW engineering, HW engineering, and products.
The team builds critical infrastructure that begins with onboarding the latest machine learning architectures to embedded devices, optimization toolkits to optimize these models to better suit the target devices, machine learning compilers and runtimes to complete these models as efficiently as possible, and the benchmarking, analysis and debugging toolchain needed to improve on new model iterations. This infrastructure underpins most of Apple's critical machine learning workflows across Camera, Siri, Health, Vision, etc., and as such is an integral part of Apple Intelligence.
Our group is seeking an ML Infrastructure Engineer, with a focus on ML Insights and Forecasting. The role entails exploring new trends in ML architectures, getting them running with our on device stack, and building infra to enable regular coverage of these models.
Description:
We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple's vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling and analysis.
This role provides a great opportunity to bring the latest ML architectures and trends to our on device inference stack. Work includes prototyping to get new ideas working, building infrastructure to enable regular coverage, and collaborating with inference stack teams to make any changes needed to enable new architectures/features as well as deliver full machine performance.
The role further offers a learning platform to dig into the latest research about on-device machine learning, an exciting ML frontier! Possible example areas include model visualization, efficient inference algorithms, model compression, and/or ML compilers/run-time.
Key Responsibilities:
-
Explore the latest ML model architectures and prototype getting these running on device.
-
Build infrastructure to enable at scale testing of new ML features.
-
Analyze achieved performance vs roofline models on Apple's hardware.
-
Analyze telemetry data to understand how users are using ML on device.
-
Identify gaps in today's ML inference stack and work with XF teams to prioritize and address these.
-
Collaborate extensively with ML and hardware teams across Apple.
Preferred Qualifications:
Masters or Ph Ds in Computer Science or relevant disciplines.
Experience in system performance analysis and optimizing ML models for edge inference
Experience with standard ML concepts such as Transformers, CNNs or Stable Diffusion a strong plus.
Minimum Qualifications:
Bachelors in Computer Science or relevant subject areas and and 4+ years of related experience, working with ML technologies.
Experience with any ML authoring framework (Py Torch, Tensor Flow, JAX, etc.), particularly on-device ML frameworks such as CoreML, TFLite or Execu Torch.
Strong programming and software design skills in Python.
In depth knowledge of quality practices and fundamentals, including test planning, automation, and performance evaluation.
Solid ML fundamentals including training regimes, evaluation and deployment/inference.
Excellent collaboration and communication skills.
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 $139,500 and $258,100, 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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