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Apple AIML - Staff ML Infrastructure Engineer United States, California 101925456
21.04.2025
- Drive large-scale training initiatives to support our most complex models.- Operationalize large-scale ML workloads on Kubernetes.- Enhance distributed cloud training techniques for foundation models.- Design and integrate end-to-end lifecycles for distributed ML systems- Develop tools and services to optimize ML systems beyond model selection.- Architect a robust MLOps platform to support seamless ML operations.- Collaborate with cross-functional engineers to solve large-scale ML training challenges.- Research and implement new patterns and technologies to improve system performance, maintainability, and design.- Lead complex technical projects, defining requirements and tracking progress with team members.- Mentor engineers in areas of your expertise, fostering skill growth and knowledge sharing.- Cultivate a team centered on collaboration, technical excellence, and innovation.
- Bachelors in Computer Science, engineering, or a related field
- 7+ years of hands-on experience in building scalable backend systems for training and evaluation of machine learning/deep learning models
- 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, Ray, PySpark
- 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
- Proficient in working with and debugging accelerators, like: GPU, TPU, AWS Trainium
- Proficient in ML training and deployment frameworks, like: JAX, Tensorflow, PyTorch, TensorRT, vLLM
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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