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AI/ML Engineer (GenAI), G&A Solutions Engineering (GSE)

Apple

AI/ML Engineer (GenAI), G&A Solutions Engineering (GSE)

Apple

Austin, TX

·

On-site

·

Full-time

·

2d ago

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The G&A Solutions Engineering organization at Apple primarily focuses on creative ways to engineer business solutions to meet growing needs of Apple's Finance, i Tunes, Sales, Retail, and Services organizations. At core, our portfolio comprises of engineered custom solutions to process high volume transactions from Apple Pay, i Tunes, Ads, App Store, i Phone Activations to Sales from Retail, Online, and Resellers. These solutions are based on cutting edge enterprise technologies ranging from Distributed Systems, Microservices, Java, Spring/Boot, Oracle, MongoDB, AWS services to AI/ML, Generative AI, and Blockchain. Accurately processing such high volume transactions is our core strength.

Description

The i Recon Payments team is seeking a highly motivated AI/ML Engineer to help build our next-generation payments platform. In this role, you will blend classical ML with cutting-edge Generative and Agentic AI to transform how we process transactional data at scale.

","responsibilities":"You will act as a technical catalyst, modernizing complex product architectures to enable full observability and autonomous workflows for reconciliation, invoicing, and payments

We are looking for a self-starter who can navigate the intersection of financial data and Large Language Models to drive productivity and operational efficiency

Preferred Qualifications

3+ years deploying production-grade AI/ML solutions in the Fin Tech domain

2+ years building conversational assistants or autonomous agents using advanced techniques (Lang Graph, CrewAI, A2A, CoT, Re Act, Reflection)

Experience with the full LLM lifecycle including pre-training, SFT, and Reinforcement Learning techniques (RLHF, PPO, GRPO)

Demonstrated ability to quickly master emerging AI tools and integrate them into legacy stacks

Strong written and verbal communication skills with the ability to explain complex AI concepts to business stakeholders

Minimum Qualifications

2+ years of experience building machine learning solutions using supervised/unsupervised learning, classification, recommendation systems, and clustering algorithms

In-depth knowledge of transformer architecture, LLMs, and Agentic AI concepts

Hands-on experience fine-tuning Large Language Models (LLMs) using PEFT/LoRA for domain-specific tasks

Proven experience building and extending RAG, MCP (Model Context Protocol), or multi-agent frameworks (e.g., Lang Chain, Llama Index, Auto Gen)

Bachelor's degree in Computer Science, AI, Machine Learning, or relevant work experience

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .

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スクラップ

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Appleについて

Apple

Apple

Public

Apple Inc. is an American multinational technology company headquartered in Cupertino, California, in Silicon Valley, best known for its consumer electronics, software and online services.

10,001+

従業員数

Cupertino

本社所在地

$3.5T

企業価値

レビュー

3.9

10件のレビュー

ワークライフバランス

2.5

報酬

4.2

企業文化

3.8

キャリア

3.5

経営陣

3.2

72%

友人に勧める

良い点

Great benefits and compensation

Talented colleagues and supportive teams

Learning opportunities and mentorship

改善点

Work-life balance challenges

High stress and pressure

Fast-paced environment

給与レンジ

11,365件のデータ

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Data Scientist ICT2

0件のレポート

$121,979

年収総額

基本給

-

ストック

-

ボーナス

-

$103,682

$140,276

面接体験

3件の面接

難易度

3.3

/ 5

期間

28-42週間

内定率

33%

体験

ポジティブ 33%

普通 0%

ネガティブ 67%

面接プロセス

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience