Jobs
Benefits & Perks
•Learning and development stipend
•Health, dental, and vision coverage
•Top Tier compensation with equity
•Remote work flexibility
•Annual team offsites
•Parental leave program
Required Skills
Airflow
Apache Spark
SQL
Distinguished Engineer
- ML Compute Infrastructure
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because each of us believes we can create something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something!
- As part of the Machine Learning Platform Technologies
- ML Compute organization, you'll connect the world's best researchers with the world's best AI infrastructure to take on the most challenging problems in machine learning and build the rock-solid foundation for some of Apple's most innovative products. And this is Apple, so your team will innovate across the entire stack: hardware, software, algorithms - it's all here.
About the Role
We are seeking a Distinguished Engineer to provide technical leadership in building and evolving next-generation AI infrastructure at Apple. In this role, you will shape the architecture and long-term technical strategy for large-scale training and inference systems, working at the intersection of AI research, systems, and cloud infrastructure. Your work will directly influence how frontier and production models are trained, deployed, and scaled across diverse accelerator platforms.
Responsibilities
- Set the technical vision and define the roadmap for frontier AI infrastructure spanning a multi-cloud heterogeneous compute fleet
- Design and build distributed systems for job scheduling, cluster management, and cost governance
- Partner closely with ML researchers and engineers to scale and optimize end-to-end performance of AI training and inference workloads
- Establish connections with cross-functional partners, collaborating with teams across cloud infrastructure, business operations, finance, and engineering
Minimum Qualifications
- Bachelor's degree in Computer Science, relevant technical field, or equivalent practical experience
- 15 years of experience designing and building very large-scale distributed systems
- Proficiency in at least 1 backend language (e.g., Python, C++, Go, Rust)
- Proficiency in cloud-native architectures and compute orchestration platforms (e.g., Kubernetes)
- Hands-on experience working with ML accelerators such as GPUs and TPUs
- Track record of mentoring senior engineers and setting long-term architectural vision across orgs
Preferred Qualifications
- Master's degree or PhD in Computer Science or related technical fields
- Experience in running distributed training and/or inference workloads in production
- Expertise in ML systems performance profiling, debugging, and optimization
- Expertise in deep learning frameworks (e.g., Py Torch, JAX) and their underlying architectures
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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