Want to get hired at Apple?
Staff ML Infrastructure Engineer, Machine Learning Compute
Apple
Santa Clara, California, United StatesOn Site
Original Job Summary
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
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Review cloud-native architecture concepts.
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Practice distributed systems problem-solving.
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Experiment with Apache Spark and Ray.
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Brush up on Kubernetes and containerization.
Behavioral Questions
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Describe teamwork in challenging projects.
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Explain your leadership in technical mentorship.
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Discuss conflict resolution in cross-functional teams.
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Share examples of handling project setbacks.