Applied AI/ML Software Engineer.

Are you passionate about Machine Learning and AI, and eager to apply your expertise to solve real-world problems at Apple’s incredible scale? Do you want to see your work translated into direct impact on iPhone, iPad, Mac, AirPods, Watch, and more? Come join us in in developing, shipping, and maintaining AI/ML and Generative AI services — including the infrastructure, evaluation pipelines, and integration workflows that provide cutting-edge features to support Apple’s hardware product development teams, helping bring amazing, groundbreaking products and innovations to life.

We are the Human Research and Engineering Solutions (HRES) AI/ML team, and we build and deliver software supporting the development of Apple’s unparalleled hardware product line. Our software is used by Apple engineers, factory teams, and third-party accessory manufacturers to develop and debug their systems, with high visibility throughout the company.

Description

As a Software Engineer in our team, you will work with a diverse array of cross-functional partners throughout Apple on challenging projects incorporating Machine Learning and Generative AI. The software you build will be instrumental in solving difficult challenges, providing data insights, and driving decision-making within Hardware Engineering and beyond. We move at a fast pace, iterate quickly, and work side-by-side with our customers to ensure we’re building the most effective solutions possible.

Minimum Qualifications

Bachelor’s Degree in Computer Science, Computer Engineering, related field, or equivalent work experience
3+ years professional software engineering experience working in Python or other object-oriented programming language(s)
Demonstrated ability to write applications in a high-level programming language like Python, Ruby, Java, etc.
Excellent written and verbal communication skills to both technical and non-technical audiences

Preferred Qualifications

Master’s degree in Computer Science, Computer Engineering, related field, or equivalent work experience
Experience building with LLMs, designing and training custom ML models, and developing RAG/agentic pipelines
Experience with data analysis, processing, analytics, and visualization to drive data-based decision making
Experience with evaluating complex AI systems, producing actionable hypotheses, and assessing their validity
Exposure or interest in leveraging Kubernetes and other cloud-based deployment platforms to deliver applications reliably at a high velocity
Ability to architect complex systems in a reusable, modular way
Curiosity to learn new technologies and passion for sharing that knowledge with others