Jobs

Software Engineering Manager, Machine Learning Systems Infrastructure - SIML, ISE
Seattle, WA
·
On-site
·
Full-time
·
2w ago
Compensation
$188,200 - $325,500
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Healthcare
•401k
•Equity
•Learning
Required Skills
Full-stack development
Java
Go
Python
C/C++
Machine learning
Systems engineering
System design
Do you think Computer Vision and Machine Learning can change the world? Do you think it can transform the way millions of people collect, discover and share the most special moments of their lives? We truly believe it can. And we are looking for hardworking engineers who can contribute to building the ecosystem of tooling necessary to create these exciting technologies.
We are the System Intelligent and Machine Learning (SIML) group that provides foundational computer vision and machine learning technologies to Apple's ecosystem. Our work is behind essential features such as Camera, Text & Handwriting recognition, and Apple Intelligence experiences (Image Playground, Writing Tools, Smart Script, Math Notes..).
Description:
In this role, you will be building infrastructure to support product-focused machine learning projects. You will contribute significantly in a hands-on technical manner while managing a team to build systems that leverage machine learning to index terabytes of data for projects in domains like image generation, LLMs, computer vision, natural language processing, human-computer interaction and text recognition. You will define and build out systems for analysis of failure modes of algorithms built upon this data, and for reporting overall benchmarking results for model comparisons. The technology you and your team builds will play a major role in defining important datasets, ingestion of annotated/inferred data into our systems, and making the data available to machine learning scientists in a seamless manner. This role requires a diverse set of skills, from tackling low-level distributed computing challenges at bare metal, to contributing to internal client user experiences by building stable interfaces, and everything in between.
As the ideal candidate, you enjoy variety, and are passionate about working on new things on a frequent basis. You love working with a large number of people across teams throughout the company, and driving solutions that take multiple partners into account. You are either a machine learning industry pro, or an outstanding engineer wanting to expand your horizons and learn more about the nitty gritty of how ML projects are launched from inception to release.
Preferred Qualifications:
Domain experience in machine learning, AI, computer vision, or a related field (computer graphics, image processing, multimedia, etc.).
Experience with macOS and/or iOS development and familiarity with UNIX-based systems.
Ability to provide publicly-available samples of work done, or shown success in coding competitions/hackathons is desired.
Familiarity with Objective-C.
Minimum Qualifications:
Bachelors, Masters, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or equivalent experience.
5+ years of experience in full-stack development with 2+ years in a managerial, or demonstrated lead role.
Experience in Java, Go and/or Python, and C/C++.
Solid working knowledge of machine learning fundamentals.
Proven experience in systems engineering fundamentals and system design, and can show strong expertise in one or more systems engineering stacks.
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 $188,200 and $325,500, 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.
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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
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Principal/L7
Senior/L5
Staff/L6
Junior/L3 · Data Scientist ICT2
0 reports
$121,979
total / year
Base
-
Stock
-
Bonus
-
$103,682
$140,276
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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