below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$202,800–$254,750.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
3497 open roles
on FindRole.
Listed pay typically runs
$174,149–$277,600
across 2702 roles with salary data.
JOB TITLE: Machine Learning Engineer, Apple Store Online
The Machine Learning Engineer, Apple Store Online joins the Online Retail Decision Automation team to research and develop next-generation algorithms for the digital retail experience. This role involves building scalable, production-ready machine learning solutions for product search, recommendation systems, personalization, and Generative AI. You will take algorithms from initial concept through deployment while improving ML infrastructure and tooling. Key responsibilities include mentoring other engineers and collaborating with cross-functional teams to solve retail problems. Required skills include proficiency in Python, Java, or C++, experience with distributed systems, and big data technologies like Spark, SQL, Snowflake, or Hadoop. Preferred expertise includes Deep Learning, Reinforcement Learning, and frameworks such as TensorFlow, Keras, and PyTorch to enhance the online shopping journey.
What does a Machine Learning Engineer earn?
Median $235750 from 323 postings across 48 companies.
Research and develop next-generation algorithms for product search and recommendation systems.
Build and deploy scalable, production-ready machine learning solutions for retail customers.
Develop models for personalization, including evidence, messaging, and marketing.
Implement Generative AI solutions and RAG-based architectures.
Build and maintain large-scale data processing pipelines using big data technologies.
Optimize Apple-wide machine learning systems and infrastructure.
Mentor other Machine Learning Engineers on the team.
Manage the full ML model lifecycle from prototyping and training to deployment and monitoring.
What we're looking for
Proficiency in one or more object-oriented programming languages such as Python, Java, or C++.
Experience building highly scalable distributed systems.
Hands-on experience building data processing pipelines, large-scale machine learning systems, and big data technologies like Spark, SQL, Snowflake, or Hadoop.
Bachelor's degree in a quantitative field such as Computer Science, Applied Mathematics, or Statistics.
Bachelor's degree in a quantitative field with a focus on AI in coursework.
Understanding of the machine learning model lifecycle from prototyping to deployment and monitoring (preferred).
Experience in Recommender Systems, Personalization, Search, Computational Advertising, or NLP including RAG-based Generative AI and transformer architecture (preferred).
Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications (preferred).
Python
Java
C++
Machine Learning
Generative AI
PyTorch
TensorFlow
Keras
Spark
SQL
Snowflake
Hadoop
Natural Language Processing
Transformer Architecture
Reinforcement Learning
Deep Learning
Distributed Systems
RAG
Feature Engineering
Python
Java
C++
Machine Learning
Deep Learning
PyTorch
TensorFlow
Keras
Spark
SQL
Snowflake
Hadoop
Generative AI
RAG
Transformer Architecture
Natural Language Processing
Recommender Systems
Distributed Systems
Data Processing Pipelines
Reinforcement Learning
Machine Learning
NLP
Deep Learning
Information Retrieval
Reinforcement Learning
Statistics
Optimization
Forecasting
Agile
Production Systems
Design of Experiments