Job Description

We are looking for a passionate and experienced Software Engineer to help build next- generation of Applied Machine Learning Platform at Apple China. Applied Machine Learning Platform team provides backend services and infrastructure for various Machine Learning and Data Science teams to train, build, deploy and inference models at scale to prevent Fraud on multiple Apple Platforms like Apple Pay, Apple Media Products, App Store, Online Store, Retail, AppleCare and Manufacturing. In addition to preventing Fraud, this platform is responsible for driving Operations and Logistics for Online Store, AppleCare and Retail. Our team within the greater AiDP Platform team is the Core Services which is a backbone of the platform, responsible for handling thousands of transactions per second in a distributed manner.

This is a role of a Sr Software Engineer who has deep systems thinking to design, build and enhance scalable and highly concurrent ML/AI serving platform. Knowledge of Python, Machine Learning concepts, tools and packages is a must. If you’re excited about building production-grade platform and solving hard distributed systems problems, this is your opportunity to make a lasting impact at scale.

Preferred Qualifications

Excellent written and verbal communication skills on both technical and non-technical topic
Exposure to Ray, KServe, Triton Or other inference frameworks
Ability to debug complex cross-platform issues and optimize performance
Ability to debug and improve ML workflow tuning for high accuracy
Knowledge of using GenAI to build solutions to improve productivity of developers, users, and business
Self-directed, self-motivated and detail oriented with ability to come up with good design proposals and thorough analysis of production issues

Minimum Qualifications

6+ years of software development experience
4+ years of Python or Java expertise building Production Applications
Solid understanding of concurrency, threading, multiprocessing and their practical trade-offs in high-throughput production systems
Strong understanding of language internals and their implications in highly concurrent systems
Deep knowledge of ML/AI frameworks and ecosystem
Strong understanding of computer science fundamentals, including data structures and algorithms
Proficiency in Containerization technologies like Kubernetes and CNCF technologies
Proficiency in profiling, optimizing, debugging applications and libraries
Bachelor’s degree or equivalent in Computer Science or similar discipline or experience