ML Infrastructure Software Engineer

1 Month ago • 3 Years + • Devops

Job Summary

Job Description

Join Apple's Silicon Technologies group as an ML Infrastructure Software Engineer. You will be responsible for crafting and building the technology that fuels Apple's devices. This role focuses on enabling the deployment and integration of AI models supporting various domains. Key responsibilities include deploying, optimizing, and integrating industry-standard AI models within internal infrastructure for silicon design workflows, collaborating with teams to define model needs and benchmarking standards, managing fine-tuning and model conversion pipelines, implementing monitoring for efficient model deployment, and contributing to compute planning and hardware decisions, including evaluating third-party silicon and supporting internal chip solutions.
Must have:
  • Deploying AI models
  • Optimizing AI models
  • Integrating AI models
  • Collaborating with teams
  • Managing model pipelines
  • Monitoring model deployment
  • Contributing to compute planning
  • Evaluating silicon

Job Details

Do you love creating elegant solutions to highly complex challenges? Do you intrinsically see the importance in every detail? As part of our Silicon Technologies group, you’ll help build AI-driven solutions that solve pressing business challenges. You’ll ensure Apple products and services can seamlessly and efficiently handle the tasks that make them beloved by millions. Joining this group means you’ll be responsible for crafting and building the technology that fuels Apple’s devices.\n\nWe are looking for an individual who is passionate about joining Apple’s engineering team as an ML Infrastructure Software Engineer to enable the deployment and integration of AI models supporting our domains.

In this highly visible role, your primary responsibilities will include: - Deploying, optimizing, and integrating industry-standard AI models within internal infrastructure to support silicon design workflows. - Collaborating with internal teams to evaluate model needs, define selection and benchmarking standards, and ensure our infrastructure remains state-of-the-art by tracking industry advancements. - Managing pipelines for fine-tuning and model conversion, and implementing monitoring to ensure scalable and efficient model deployment. - Contributing to compute planning and hardware decisions, including evaluating third-party silicon and supporting adoption of internal chip solutions.

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