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Software Engineer AI ML

Apple

Austin, Texas, United StatesOn Site

Original Job Summary

Overview

Apple is looking for a Software Engineer AI ML to join the AI & Data Platforms team. At Apple, your work will drive innovative AI models and systems that enhance products and services worldwide.

Role Responsibilities

You will build and scale best in class data and reporting applications with minimal latency and outstanding user experience. This includes:

  • Engaging with key business partners to understand needs
  • Driving functional and technical discussions with development teams
  • Designing and owning end-to-end applications

Machine Learning Engineer Focus

In this role, as a Machine Learning Engineer, you will:

  • Build intelligent systems to democratize AI across solutions
  • Develop and deploy innovative AI models impacting Apple’s products
  • Implement robust ML infrastructure for data processing and model serving
  • Design automated ML pipelines for rapid experimentation
  • Optimize model compression techniques

Minimum Qualifications

  • BS in Computer Science or related field
  • 3+ years of machine learning engineering experience
  • Experience with feature engineering, model training, serving, and monitoring
  • Proficiency in frameworks like PyTorch or TensorFlow

Preferred Qualifications

  • Experience in anomaly detection, forecasting and related methodologies
  • Proficiency with Python and efficient SQL
  • Strong software engineering principles including testing and code reviews
  • Familiarity with transformer models such as BERT and GPT
  • Experience with data visualization tools (Superset, Streamlit, Tableau)

Key skills/competency

  • Machine Learning
  • AI
  • Python
  • TensorFlow
  • PyTorch
  • Data Engineering
  • Software Engineering
  • Model Deployment
  • Data Visualization
  • Automation

How to Get Hired at Apple

🎯 Tips for Getting Hired

  • Customize your resume: Highlight AI and ML projects at Apple.
  • Research Apple's culture: Understand their innovation and values.
  • Tailor your skills: Emphasize Python, TensorFlow, and PyTorch expertise.
  • Prepare for interviews: Practice technical and behavioral questions.

📝 Interview Preparation Advice

Technical Preparation

Review ML frameworks like TensorFlow and PyTorch.
Practice coding and algorithm optimization.
Study ML pipeline automation best practices.
Brush up on model deployment techniques.

Behavioral Questions

Describe a challenging team project.
Explain a time you solved a critical problem.
Detail handling tight deadlines.
Share an experience with cross-functional collaboration.