Software Engineer, Generative AI & ML, Customer Systems

Apple Inc

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Quick summary

Work type
On-site
Location
Austin, TX
Posted
159 days ago
Freshness
Confirmed live today

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Salary context

How this pay compares to similar roles

Similar $205k
$140k $268k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $169,050–$241,750.

Based on 240 similar postings.

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About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 3497 open roles on FindRole.

Listed pay typically runs $174,149–$277,600 across 2702 roles with salary data.

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At a glance

TL;DR · Software Engineer, Generative AI & ML, Customer Systems

The Software Engineer - Generative AI & ML, Customer Systems joins the Customer Support AI team to build multi-turn, conversational, and agentic applications. You will contribute to model development and fine-tuning workflows for generative AI features while designing and evaluating retrieval strategies to ground large models in product-relevant data. Your daily work involves prototyping and benchmarking multi-agent collaboration systems for structured reasoning tasks and partnering with data and platform engineers to ensure scalable deployment and monitoring. You must utilize machine learning libraries like transformers and datasets, and possess experience with RAG architectures, vector-based retrieval systems, and cloud environments like AWS or GCP. The role focuses on enhancing a multi-modal platform to improve latency, cost, and customer experience across numerous lines of business.

What does a Software Engineer earn in Texas?

Median $178175 from 187 postings across 44 companies.

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What you'll do

  • Develop and fine-tune generative AI models for customer support applications.
  • Design retrieval strategies to integrate product-relevant data into large language models.
  • Prototype and benchmark multi-agent systems for efficient structured reasoning tasks.
  • Collaborate with engineers to ensure scalable deployment of AI solutions in cloud environments.
  • Enhance latency, cost efficiency, and overall customer experience through innovative research.
  • Integrate voice capabilities by working with speech-to-text and text-to-speech systems.

What we're looking for

  • 4+ years of hands-on experience in ML and backend engineering.
  • 1+ year of experience in training, fine-tuning, or evaluating LLMs.
  • Proficiency in machine learning libraries such as transformers and datasets.
  • Bachelor's or Master's degree in Computer Science, Machine Learning, or related field.
  • Experience with deploying to cloud environments (AWS, GCP).
  • Foundational understanding of RAG architectures and vector-based retrieval systems.

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