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Apple AIML - Staff ML Infrastructure Engineer Machine Learning Compute United States, West Virginia 876606301
05.09.2025
- Optimize platform efficiency and throughput by improving resource management capabilities with schedulers like Apache YuniKorn and Kueue.- Integrate new features from core distributed computing and ML frameworks into the platform, offering them to production users and providing support.- Enhance the platform's scalability, performance, and observability through improved monitoring and logging.- Drive the architectural evolution of the platform by adopting modern, cloud-native technologies to improve system performance, efficiency, and scalability.- Reduce dev-ops efforts by automating and streamlining operational processes.- Mentor engineers in areas of your expertise, fostering skill growth and knowledge sharing.
- Bachelors in Computer Science, engineering, or a related field.
- 4+ years of hands-on experience building and managing large-scale data and ML infrastructure.
- Proficient in relevant programming languages, like Python or Go.
- Strong expertise in distributed systems, reliability and scalability, containerization, and cloud platforms.
- Proficient in cloud computing infrastructure and tools: Kubernetes, Apache Spark, and Ray.
- Ability to clearly and concisely communicate technical and architectural problems, while working with partners to iteratively find solutions.
- Advance degrees in Computer Science, engineering, or a related field.
- Hands-on experience with cloud-native resource management and scheduling tools like Apache YuniKorn.
- Experience with advanced architecture for distributed data processing and ML workloads.
- Proficient in working with and debugging accelerators, like: GPU, TPU, AWS Trainium.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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