Apple

Apple

Posted via Apple Careers

Software Engineering (AI/ML), Retail and Marcom Engineering

Always Hiring

Posted Oct 22, 2026

Role at a glance

Job function
AI & Data Generative AI Engineering
Salary
Not yet verified Check the description for pay details; an amount or pay period has not been verified.
Location
Austin, Texas, United States Sunnyvale, California, United States
Experience
5 years of hands-on experience implementing AI/ML models in enterprise systems.
Education
BS or MS in Engineering, Computer Science, or a related field, or equivalent practical experience.

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Role Summary

AI-generated

The Senior AI/ML Engineer builds and deploys intelligent systems for Apple's creative marketing team. The role spans the machine-learning lifecycle and the development of production AI/ML solutions, including GenAI, LLM, RAG, and conversational AI applications.

What You'll Do

  • Drive the machine-learning project lifecycle and deliver AI-powered solutions.
  • Design and develop virtual assistants using Conversational AI platforms.
  • Work with business stakeholders to identify AI/ML opportunities and develop analytic solutions using LLM technologies.
  • Build and deploy AIOps solutions for clustering, classification, anomaly detection, and capacity prediction.

Generated from the employer's posting. Verify important details before applying.

View full posting

Qualifications

Required: 5 years of hands-on experience implementing AI/ML models in enterprise systems; knowledge of supervised and unsupervised learning, deep learning, and anomaly detection; expertise in NLP, NLU, and Conversational AI, including intent recognition, dialogue management, and natural language generation; production experience with GenAI solutions (LLMs and RAG) and understanding of LLM architectures; mastery of Python, Pandas, NumPy, TensorFlow, and PyTorch; ability to integrate AI and bot systems with backend systems, databases, and APIs; troubleshooting and analytical skills in distributed environments; BS or MS in Engineering, Computer Science, or a related field, or equivalent practical experience.

Preferred

  • Hands-on experience building and deploying Graph RAG pipelines, including graph databases and vector stores.
  • Knowledge of DevOps practices, including CI/CD pipelines, infrastructure as code (e.g., Terraform), containerization (Docker), and...
  • Knowledge of SRE principles, including SLIs/SLOs, monitoring and alerting, incident response, root cause analysis, and production...
  • Familiarity with RAG benchmarking and evaluation methodologies, including faithfulness, context recall, LLM-as-judge, and golden datasets.
  • Experience fine-tuning LLMs (e.g., LoRA, PEFT) and knowing when to choose fine-tuning over prompting or RAG.
  • Experience building solutions with multi-modal models and agentic workflows, including tool use, orchestration, and failure handling.
  • Experience designing, building, and deploying AI/ML platforms and services at scale, handling high data volumes and traffic.
  • LLMOps experience, including production evaluation, guardrails, observability, and cost and latency optimization.

Original job description

Content provided by the employer

Summary

Do you want to help build some of the largest and most consequential enterprise and customer technology systems in the world? Join Apple’s Information Systems and Technology (IS&T) organization. IS&T is the engine behind everything Apple does for customers and for the people who build for them. It’s Apple’s central nervous system. Supporting 2.5 billion active Apple devices, processing billions of secure transactions, and keeping the technology that defines modern life running flawlessly, IS&T makes the impossible feel effortless. Do you love building solutions to handle global complexity and immense scale? Imagine what you could do here.

Retail and Marcom Engineering, an IS&T team, builds and operates the systems and experiences that connect Apple's products with its customers. The team owns the technology behind both Apple's online and physical stores and drives the interactive marketing experiences and tools that keep creative operations moving. Together, those functions deliver the technology behind every product story Apple tells and every purchase a customer makes.

Description

We're seeking a talented Senior AI/ML Engineer to build and scale the intelligent systems behind Apple's globally led creative marketing team. You will drive the end-to-end development and deployment of cutting-edge AI/ML solutions, directly influencing how millions of Apple customers experience our brand. You'll design, build, and optimize production systems involving GenAI, LLMs, Graph RAG, and multi-modal models, engineering intelligent conversational and agentic workflows that redefine what's possible. If you're ready to build and ship high-impact AI/ML solutions at a global scale, this is your opportunity.

As a Senior AI/ML Engineer, you'll design, build, and deploy intelligent experiences, driving the end-to-end machine learning lifecycle from conception to production. Partnering with business and engineering stakeholders, you'll translate complex requirements into scalable AI/ML solutions, developing robust pipelines and applications that leverage LLM and GenAI technologies to unlock new insights at scale.

Your hands-on expertise will help establish engineering best practices for LLM, RAG, and conversational AI implementations, ensuring high performance, reliability, and maintainability across our services. You'll also build and deploy advanced AIOps solutions, implementing models for clustering, classification, anomaly detection, and capacity prediction to optimize our systems.

Responsibilities

AI-Powered Solutions: Drive the complete machine learning project lifecycle, ensuring best practices and flawless software delivery.
Intelligent Assistants: Lead the design and development of virtual assistants using Conversational AI platforms, creating impactful and intuitive experiences.
Data-Driven Insights: Collaborate with business stakeholders to identify AI/ML opportunities and develop advanced analytic solutions leveraging LLM technologies, transforming data into actionable strategies.

Minimum Qualifications

5 years of hands-on experience implementing AI/ML models in enterprise systems.
Knowledge of core AI/ML concepts, including supervised and unsupervised learning, deep learning, and anomaly detection.
Expertise in NLP, NLU, and Conversational AI, including designing and deploying bots with intent recognition, dialogue management, and natural language generation.
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 (Pandas, NumPy, TensorFlow, PyTorch).
Ability to integrate AI and bot systems with backend systems, databases, and APIs to deliver end-to-end solutions.
Troubleshooting and analytical skills, including diagnosing complex issues in distributed environments.
BS or MS in Engineering, Computer Science, or a related field, or equivalent practical experience.

Preferred Qualifications

Hands-on experience building and deploying Graph RAG pipelines, including graph databases and vector stores.
Knowledge of DevOps practices, including CI/CD pipelines, infrastructure as code (e.g., Terraform), containerization (Docker), and Git-based workflows for automated build, test, and deployment of ML services.
Knowledge of SRE principles, including defining SLIs/SLOs, monitoring and alerting, incident response, root cause analysis, and building for reliability in production systems.
Familiarity with RAG benchmarking and evaluation methodologies (e.g., faithfulness, context recall, LLM-as-judge, golden datasets).
Experience fine-tuning LLMs (e.g., LoRA, PEFT) and knowing when to choose fine-tuning over prompting or RAG.
Experience building solutions with multi-modal models and agentic workflows (tool use, orchestration, failure handling).
Experience designing, building, and deploying AI/ML platforms and services at scale, handling high data volumes and traffic.
LLMOps experience, including production evaluation, guardrails, observability, and cost and latency optimization.
Experience building AIOps solutions such as clustering, classification, anomaly detection, and capacity prediction.
Familiarity with cloud-native and GPU-backed inference environments (e.g., Kubernetes, model serving).
Track record of mentoring engineers, defining reference architectures, and setting best practices for LLM, RAG, and conversational AI.
Experience applying GenAI to content, creative, or marketing workflows.
Communication and collaboration skills, with the ability to explain technical concepts to technical and non-technical audiences.

Pay & Benefits — Sunnyvale, California, United States

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $150,400 and $277,600, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Application Deadline

Apple accepts applications to this posting on an ongoing basis.

Apple

About the company

Apple

Large Enterprise

Apple Inc. is a global technology company known for its innovative products and services, including the iPhone, iPad, Mac computers, and Apple Watch. Founded in 1976, Apple has continuously pushed the boundaries of design and functionality, earning a reputation for high-quality consumer electronics and software solutions like iOS and macOS. With a strong commitment to user experience and privacy, Apple also leads in digital services, offering platforms such as the App Store, Apple Music, and iCloud. The company's focus on sustainability and corporate responsibility further enhances its standing as a leader in the technology sector.