Overview
On Site
Full Time
Skills
User Experience
Data Science
Open Source
Collaboration
Software Release Life Cycle
DevOps
Use Cases
Application Development
Continuous Integration and Development
Management
UI
Regression Analysis
Continuous Integration
Continuous Delivery
Shell Scripting
Linux
Version Control
Git
Computer Science
Quality Assurance
Automated Testing
Software Development
Java
Python
Innovation
Apache Cassandra
Apache Spark
Apache Flink
Apache Kafka
Apache Solr
Extract
Transform
Load
Software Testing
API
Acceptance Testing
Machine Learning (ML)
Docker
Kubernetes
Performance Testing
Apache JMeter
IaaS
Amazon Web Services
Google Cloud Platform
Google Cloud
Cloud Computing
Generative Artificial Intelligence (AI)
Accessibility
Testing
Job Details
Join Apple's Applied Machine Learning Engineer Services team, where innovative ideas rapidly become exceptional products that impact millions of users worldwide. We're looking for a passionate Software Development Engineer in Test to help ensure our machine learning platforms and GenAI solutions meet Apple's high standards for quality, accessibility, and user experience.
Description Our Applied Machine Learning Engineer Services team supports the development of large-scale data science and enterprise generative AI applications that serve multiple Apple lines of business. We contribute to open-source projects, collaborate across the entire company, and work with Apple-scale data to create meaningful customer experiences. In this role, you will provide build, release, and quality assurance services to a diverse team of engineers, data scientists, DevOps professionals, and managers who are committed to delivering reliable, inclusive technology solutions on the frontier of the latest technologies. This role involves creating and maintaining tools, frameworks and services to address emerging needs of the team in the areas of Continuous Integration and Delivery, as well as manual product validation.
Responsibilities
Minimum Qualifications
Preferred Qualifications
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 .
Description Our Applied Machine Learning Engineer Services team supports the development of large-scale data science and enterprise generative AI applications that serve multiple Apple lines of business. We contribute to open-source projects, collaborate across the entire company, and work with Apple-scale data to create meaningful customer experiences. In this role, you will provide build, release, and quality assurance services to a diverse team of engineers, data scientists, DevOps professionals, and managers who are committed to delivering reliable, inclusive technology solutions on the frontier of the latest technologies. This role involves creating and maintaining tools, frameworks and services to address emerging needs of the team in the areas of Continuous Integration and Delivery, as well as manual product validation.
Responsibilities
- Design and implement comprehensive test automation frameworks for large-scale, distributed applications, ensuring quality across UI, API, and backend systems
- Develop and execute testing strategies that consider diverse user needs, including accessibility requirements and various use cases
- Create and maintain tools that enhance application development, deployment, and monitoring processes
- Define, setup and maintain reliable continuous integration and deployment pipelines and develop key quality gate implementations for them
- Champion quality practices by integrating testing frameworks with CI/CD pipelines and promoting clean coding standards
- Monitor and analyze test results, identifying patterns and opportunities for improvement
- Contribute to infrastructure management and configuration solutions that support our testing ecosystem
Minimum Qualifications
- Strong foundation in software systems and acceptance testing
- 2+ years of professional experience in software quality engineering, test automation, or software development with Java or Python
- Hands-on experience developing automated test frameworks (UI, API, integration, or regression)
- Hands-on experience with CI/CD tools and systems
- Proficient configuring application services and shell scripting in Linux environments
- Experience with version control systems (e.g., Git)
- Bachelors in Computer Science or similar or equivalent work experience
Preferred Qualifications
- 3+ years of professional experience in software quality engineering, test automation, or software development with Java and Python
- Excellent interpersonal skills, a passion for innovation and quality with strong sense of project ownership
- Practical experience testing distributed systems (Cassandra, Spark, Flink, Kafka, Solr) and ETL pipelines
- Strong foundation in software testing principles and clean coding practices with proven experience of defining strategies for integration, system, API contract, security, performance and acceptance testing
- Understanding of general Machine Learning as well as GenAI concepts and lifecycle processes
- Familiarity with containerization technologies (Docker, Kubernetes)
- Background in performance testing using tools like Gatling or JMeter
- Experience using Cloud infrastructure (e.g., AWS, Google Cloud, public cloud)
- Ability to understand and use modern GenAI development enhancement tools like Claude Code or Cursor
- Knowledge of accessibility testing practices and inclusive design principles
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 .
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.