Jobs

AIML - Staff ML System Engineer, ML Platform Technologies (MLPT)
Santa Clara, CA
·
On-site
·
Full-time
·
1mo ago
Benefits & Perks
•Parental leave program
•Top Tier compensation with equity
•Wellness benefits
•Health, dental, and vision coverage
Required Skills
Python
TensorFlow
Airflow
About the Role
Want to build the machine learning platform that engineers rely on to develop next-generation Apple Intelligence products and services? As a machine learning engineer on our team, you will create platforms and tools to enable performant, scalable ML workload for Apple's AI-driven experiences. Join our team of highly skilled, impact-focused engineers! This role also includes opportunities to open source your work and publish at top ML conferences.
Description
We're searching for strong machine learning engineers to help build next-generation platform for training deep learning models at scale. You'll be part of a team of distributed systems and machine learning experts, focusing on reliability, scalability and performance of ML related workloads including model training, inference and data processing.
We're looking for candidates with polished coding skills as well as passion for distributed systems and machine learning. In exchange, we offer a respectful work environment, flexible responsibilities, and access to world-class experts and growth opportunities-all at one of the best companies in the world.
Key Responsibilities
- Design and develop components for our centralized, scalable ML platform
- Push the limits of existing solutions for large-scale ML workloads
- Develop novel techniques to circumvent the limitations of these solutions
- Deploy your techniques on high-impact tasks from our partners across the company building new Apple Intelligence products and services
- Publish novel work at top ML conferences and release contributions as open source
Minimum Qualifications
- 7+ years of industry experience
- Bachelor's degree in Computer Science or equivalent, or a related domain
- Experience building large-scale deep learning infrastructure or platforms for distributed model training
- Experience with large-scale AI training infra components, such as accelerators, network fabrics, CUDA, NCCL, RDMA
- Strong programming skills in Python or Go
- Understanding of data structures, software design principles, and algorithms
- Experience building large-scale distributed systems with tools such as Kubernetes, Kafka, Prometheus, etc.
- Experience with deep learning frameworks, such as Py Torch, or JAX
Preferred Qualifications
- Experience working with public cloud vendors such as AWS, GCP, Azure
- Experience developing model parallel and data parallel training solutions and other training optimizations
- Familiarity with recent developments in foundation model architectures for language and multimodal
- Publication record at ML conferences such as MLSys, NeurIPS, etc.
- Advanced degree in Computer Science or equivalent, or a related field
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
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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