Software Engineer in Test -AI/ML

Socket.dev; Seattle (WA); On-site; USD 140,000 - 190,000; Full time

Job summary

Apple Services Engineering is seeking a Software Developer In Test to build developer tools and test frameworks for backend services and ML pipelines. You will lead cross-functional projects, design automated tests, and drive quality across the SDLC on a fast-moving team.

The role requires hands-on expertise in Java or Python, designing testing frameworks for distributed systems, and mentoring peers. Strong collaboration and communication are essential to deliver high-quality services at scale.

Qualifications

• Bachelor’s degree with 5+ years, or Master’s with 3+ years, of experience in software development and/or test automation, including at least 3 years leading complex, distributed systems.
• Proficiency in Java, Python or similar programming languages.
• Experience in designing and implementing testing frameworks for distributed systems, service-layer testing, including backend APIs, data processing, and infrastructure components.
• Passion for quality engineering and delivering creative approaches for testing machine learning algorithms and large scale distributed data systems.
• Impeccable communication skills and ability to effectively collaborate with multiple stakeholders across organizations and project timelines.
• Highly organized, creative, self-motivated, and passionate about achieving results.
• Excited about the possibilities unlocked by AI and ML technologies
• Advocacy for a positive customer experience.

Responsibilities

• Design, implement and maintain automation tests, testing & development frameworks and tooling to support various backend services and machine learning models and pipelines.
• Analyze, recommend, and implement best practices for coding guidelines and design principles, process workflow, quality gates, CI/CD process, etc.
• Partner with cross functional teams to define and drive quality assurance best practices, techniques and methodologies needed to enhance productivity and quality.
• Identify process and architecture inefficiencies and help drive improvements while reducing risk, fostering a culture of built-in quality and continuous testing throughout the SDLC.
• Guide tool analysis, create proof of concept models, and make recommendations to support the tools selection process.
• Mentor junior team members

Skills

Java

Python

Distributed systems

Test automation

Communication

Leadership

AI/ML enthusiasm

Education

Bachelor's degree

Master's degree

Tools

CI/CD pipelines

Job description

Imagine what we could do together. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there's no telling what we could accomplish! The Apple Services Engineering team is one of the most exciting examples of Apple's long-held passion for combining art and technology. The products we build power the intelligence behind App Store, Apple TV, Apple Games, Apple Music, Apple Podcasts, Apple Books, Apple Sports and Apple Fitness. And we do it on a massive scale, meeting Apple's high standard for quality and excellence, to deliver a huge variety of entertainment in over 50+ languages to more than 150 countries. If you are looking for an opportunity to grow in a technical capacity by leveraging your skills along with building up solid domain knowledge and automated testing strategies and systems around Apple's services offerings in the AI/ML space, we would love to talk to you!

Description

The Apple Services Engineering AI/ML quality organization is looking for a Software Developer In Test with expertise in building developer tools, test frameworks and libraries and strong experience in leading cross functional projects on a fast moving team. This role requires someone with a passion for quality engineering as well as solid software engineering skills, to deliver high quality services to Apple's customers. You will be responsible for the following:

• Design, implement and maintain automation tests, testing & development frameworks and tooling to support various backend services and machine learning models and pipelines
• Analyze, recommend, and implement best practices for coding guidelines and design principles, process workflow, quality gates, CI/CD process, etc.
• Partner with cross functional teams to define and drive quality assurance best practices, techniques and methodologies needed to enhance productivity and quality
• Identify process and architecture inefficiencies and help drive improvements while reducing risk, fostering a culture of built-in quality and continuous testing throughout the SDLC
• Guide tool analysis, create proof of concept models, and make recommendations to support the tools selection process.
• Mentor junior team members

Minimum Qualifications

Bachelor’s degree with a minimum of 5 years, or Master’s degree with a minimum of 3 years, of experience in software development and/or test automation, including at least 3 years leading complex, distributed systems.

• Proficiency in Java, Python or similar programming languages
• Experience in designing and implementing testing frameworks for distributed systems, service-layer testing, including backend APIs, data processing, and infrastructure components
• Passion for quality engineering and delivering creative approaches for testing machine learning algorithms and large scale distributed data systems
• Impeccable communication skills and ability to effectively collaborate with multiple stakeholders across organizations and project timelines
• Highly organized, creative, self-motivated, and passionate about achieving results.
• Excited about the possibilities unlocked by AI and ML technologies
• Advocacy for a positive customer experience

Preferred Qualifications

Knowledge of Big Data systems, Apache Spark is a plus

• Experience with testing or working with AI/ML systems or platforms that include ML model training or data pipelines and algorithms is a plus
• Adept at leveraging technology to solve problems, including building tooling, automating tasks, and developing supporting systems to streamline development workflows