招聘
The Siri Speech team is looking for an exceptional Machine Learning Research Engineer to create ML algorithms for Siri, Dictation, and third-party APIs running efficiently on Apple Hardware. You will help productize modern deep learning techniques running on custom Apple hardware and Private Compute Cloud, and create cutting edge products that pushes the envelope on Machine Learning for Speech Recognition, Speech Synthesis and Conversational aspects for various products.
Description:
We are looking for a talented ML Research Engineer who is excited by the prospect of working on Siri, Dictation used by millions of users. Our Engineers are creative, inspired, innovative, energetic, self motivated people who love making and shipping products. Are you one of us? You will primarily be responsible for productizing technologies that help with Accuracy, Personalization and to optimize the algorithms to each of Apple's Platforms and Devices. To succeed in this role, you must be a strong collaborator, and a creative problem solver who thrives in a fast-paced environment, working across teams and organizations.
Preferred Qualifications:
M.S, PhD in Computer Science or related field, or B.S. with equivalent industry experience
Minimum Qualifications:
Expertise in compiled languages such as Swift, C++, or Objective-C
Familiarity with model training with Py Torch, JAX or other frameworks
Applied Machine Learning practitioner:
Ability to synthesize and productize research ideas to millions of users
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 $212,000 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
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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