NLP Solutions Software Engineer

1 Month ago • All levels • Devops • $181,100 PA - $318,400 PA

Job Summary

Job Description

As part of Apple's Silicon Technologies group, this role involves building AI-driven solutions for complex business challenges. The NLP Solutions Software Engineer will craft and build technology for Apple devices, focusing on enabling generative AI applications. Responsibilities include developing LLM components, collaborating with design and AIML teams to tailor AI solutions to specific domains, serving as a technical contact for customers, and driving efficiency in chip delivery through data utilization. The role emphasizes a passion for engineering and a keen eye for detail in creating elegant solutions.
Must have:
  • Develop LLM components for generative AI applications.
  • Collaborate with design and AIML teams.
  • Resolve technical issues and provide LLM infrastructure insights.
  • Leverage data for chip delivery efficiency.

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. We are looking for an individual who is passionate about joining Apple’s engineering team as an NLP Solutions Software Engineer to enable building generative AI applications for our domains.

In this highly visible role, your primary responsibilities will include: - Developing LLM components for use in generative AI applications. - Collaborate with our internal multi-functional design teams as well as the AIML organization at Apple to understand domain-specific needs and tailor AI solutions to these domains. - Serving as the point of contact for customers, resolving technical issues, and providing insights on LLM infrastructure improvements. - Enabling the organization to leverage data and drive efficiency in chip delivery.

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