AIML - Staff ML Infrastructure Engineer, Machin... @ Apple
placeSanta Clara, California, United States
businessOn Site
Posted 5 days ago
Your Application Journey
Interview
Email Hiring Manager
***** @apple.com
Recommended after applying
Job Details
Overview
Apple is where individual imaginations gather, commit to shared values, and deliver innovative products and experiences. Join a diverse team that believes in creating something wonderful and changing lives for the better.
Responsibilities
- Lead the development of infrastructure to run large-scale workloads on the Cloud using tools such as Apache Spark, Ray, and distributed training.
- Optimize platform efficiency and throughput with resource management schedulers like Apache YuniKorn and Kueue.
- Integrate new features from core distributed computing and ML frameworks into the platform and support production users.
- Enhance scalability, performance, and observability through improved monitoring and logging.
- Drive the architectural evolution of the platform with modern, cloud-native technologies.
- Reduce dev-ops efforts through automation and streamlined operational processes.
- Mentor engineers, fostering skill growth and knowledge sharing.
Minimum Qualifications
- Bachelor's degree in Computer Science, engineering, or a related field.
- 4+ years building and managing large-scale data and ML infrastructure.
- Proficiency in programming languages such as Python or Go.
- Strong expertise in distributed systems, containerization, reliability, and scalability.
- Experience with cloud computing infrastructure and tools including Kubernetes, Apache Spark, and Ray.
- Excellent communication skills for articulating technical and architectural challenges.
Preferred Qualifications
- Advanced degree in Computer Science, engineering, or a related field.
- Experience with cloud-native resource management and scheduling tools like Apache YuniKorn.
- Expertise in advanced architecture for distributed data processing and ML workloads.
- Experience in debugging accelerators such as GPU, TPU, and AWS Trainium.
Key skills/competency
- ML Infrastructure
- Cloud-native
- Distributed Systems
- Resource Management
- Automation
- Apache Spark
- Kubernetes
- Monitoring
- Scalability
- Mentorship
How to Get Hired at Apple
🎯 Tips for Getting Hired
- Customize your resume: Highlight ML and cloud experience.
- Study Apple culture: Understand their mission and values.
- Prepare technical challenges: Practice cloud-native and distributed systems problems.
- Research role requirements: Align your skills with ML infrastructure demands.
📝 Interview Preparation Advice
Technical Preparation
circle
Review cloud-native architecture concepts.
circle
Practice distributed systems problem-solving.
circle
Experiment with Apache Spark and Ray.
circle
Brush up on Kubernetes and containerization.
Behavioral Questions
circle
Describe teamwork in challenging projects.
circle
Explain your leadership in technical mentorship.
circle
Discuss conflict resolution in cross-functional teams.
circle
Share examples of handling project setbacks.
Frequently Asked Questions
What qualifications does Apple expect for the Staff ML Infrastructure Engineer role?
keyboard_arrow_down
How important is experience with cloud-native tools at Apple?
keyboard_arrow_down
What does a typical day look like for a Staff ML Infrastructure Engineer at Apple?
keyboard_arrow_down
How does Apple support career growth for this engineering role?
keyboard_arrow_down
What technical skills are crucial for success as Staff ML Infrastructure Engineer at Apple?
keyboard_arrow_down
How does the ML Compute team at Apple function?
keyboard_arrow_down
What role do mentorship and collaboration play at Apple?
keyboard_arrow_down
What are the main responsibilities for the ML Infrastructure role at Apple?
keyboard_arrow_down
Is advanced degree necessary for the Staff ML Infrastructure Engineer position at Apple?
keyboard_arrow_down
What programming languages are important for this role at Apple?
keyboard_arrow_down