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Benefits & Perks
•Top Tier compensation with equity
•Flexible PTO policy
•Annual team offsites
•Parental leave program
•Remote work flexibility
•Health, dental, and vision coverage
Required Skills
SQL
Apache Spark
Python
About the Role
The Motion & Interaction team has created intuitive experiences for our customers through motion sensing. When you simply raise your wrist, shake your head, or move your device to interact, it's the work of engineers and scientists on this team. Our fingerprints can be found across core capabilities and experiences on i Phone, Watch, Air Pods, Vision Pro, and other Apple products.
We are a multidisciplinary team that operates at the intersection of algorithms, software, hardware, and design. We come from diverse backgrounds in signal processing, machine learning, software engineering, statistics, controls, firmware development, and more. As a member of our dynamic group, you will have a unique opportunity to work cross-functionally to develop products and features that impact the lives of millions of users worldwide on a daily basis.
We are seeking a talented, self-motivated machine learning engineer to build Apple's next-generation features and experiences using multi-modal sensing. In this role, you will ideate, design, and implement models & algorithms, while optimizing for power, memory, and performance. You will be working on motion sensing-related features, including sensor fusion and interactive technologies.
Responsibilities
- Designing and driving end to end features with specialists across the company
- Developing machine learning data pipelines for training and testing
- Deploying efficient, low-power models & algorithms
- Delivering the software through prototyping and release to our customers
- Working closely with scientists, software engineers, quality engineers, project managers, and designers throughout a product lifecycle, driving for the best possible customer experience
Minimum Qualifications
- MS, PhD, or 5+ years experience in machine learning, computer science, or related fields
- Professional experience creating and experimenting with machine learning models, preferably with time series data
- Strong proficiency in Python, machine learning tools and frameworks e.g. Py Torch, Tensor Flow
Preferred Qualifications
- Results oriented, with a proven ability to effectively prioritize and deliver tasks on schedule
- Excellent communication and collaboration skills
- Strong product sense, including the ability to balance technical feasibility with user experience
- Experience developing for embedded or real-time systems
- Experience leveraging distributed compute/storage models when the scale of data calls for it
- Experience designing and implementing interfaces between algorithms, software, and firmware
- Experience with multi-modal inputs and models, including IMU, images, video, and/or audio
Equal Opportunity
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.
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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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