Software Engineering, AI/ML, Retail and Marcom Engineering

Apple Inc

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Work type: On-site
Location: Austin, TX
Posted: 5 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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How this pay compares to similar roles

Similar $185k

$135k $235k

below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $152,437–$217,906.

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 Engineering, AI/ML, Retail and Marcom Engineering

Role Posting Log in to save

The Senior AI/ML Engineer joins the Retail and Marcom Engineering team within the Information Systems and Technology organization. In this role, you will drive the end-to-end development and deployment of intelligent systems for the global creative marketing team. You will design, build, and optimize production systems involving GenAI, LLMs, Graph RAG, and multi-modal models to create agentic workflows and virtual assistants. Key responsibilities include establishing engineering best practices for conversational AI, developing robust pipelines for data-driven insights, and building AIOps solutions for anomaly detection and capacity prediction. You will utilize Python, Pandas, NumPy, TensorFlow, and PyTorch to integrate AI with backend systems and APIs. This position solves complex technical problems by transforming marketing workflows and customer experiences through scalable, high-performance machine learning solutions.

What does a Software Engineering earn?

Median $178325 from 38 postings across 15 companies.

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Skills

Python PyTorch TensorFlow LLMs GenAI RAG Graph RAG NLP NLU Conversational AI Pandas NumPy Docker Kubernetes Terraform CI/CD LLMOps AIOps Vector Stores Graph Databases

What you'll do

Drive the end-to-end machine learning project lifecycle from initial conception to production deployment.
Design and build production systems involving GenAI, LLMs, Graph RAG, and multi-modal models.
Engineer intelligent conversational and agentic workflows to redefine customer brand experiences.
Develop robust pipelines that leverage LLM technologies to unlock actionable insights at scale.
Establish engineering best practices for LLM, RAG, and conversational AI implementations.
Build and deploy AIOps solutions for clustering, classification, anomaly detection, and capacity prediction.
Integrate AI and bot systems with backend databases and APIs to deliver end-to-end solutions.
Implement LLMOps practices including production evaluation, guardrails, observability, and cost optimization.

What we're looking for

5 years of hands-on experience implementing AI/ML models in enterprise systems.
BS or MS in Engineering, Computer Science, or a related field, or equivalent practical experience.
Expertise in NLP, NLU, and Conversational AI, including designing and deploying bots with intent recognition and dialogue management.
Experience taking GenAI solutions (LLMs and RAG) into production with a solid understanding of LLM architectures.
Mastery of Python and key AI/ML libraries and frameworks such as Pandas, NumPy, TensorFlow, and PyTorch.
Ability to integrate AI and bot systems with backend systems, databases, and APIs to deliver end-to-end solutions.
Knowledge of core AI/ML concepts, including supervised and unsupervised learning, deep learning, and anomaly detection.
Experience building and deploying Graph RAG pipelines, including graph databases and vector stores (preferred).