Machine Learning QA Engineer
Santa Clara Valley (Cupertino), California, United States
Software and Services
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring your passion and dedication to the team and there's no telling what you could accomplish. Apple services are an essential part of the Apple experience. Our users rely on services such as ApplePay, iTunes, the App Store and much much more to communicate, to access powerful applications, and to build, store and protect their memories seamlessly across all their devices. We strive to improve user experience by avoiding unnecessary friction. You will perform continuous analysis and designs and provide internal tools to help ensure that our users remain in control of their accounts, even when their credentials leave their control. The group comprises teams of Software Developers, Data Engineers, Data Analysts and Data Scientists that focus on crafting and implementing fraud prevention mechanisms, systems and tools to guarantee that new devices, software and features in our services, provide the safest experience to our customers.
- - Design and implement software for quality assurance of ML datasets and models
- - Collaborate with Data Scientists to understand data and models.
- - Applying statistical concepts to validate and QA data and models.
- - Familiarity with database modeling and data warehousing principles and SQL/noSQL
- - Possess an intuitive understanding of machine learning algorithms, supervised and unsupervised modeling techniques
- - Detail oriented, analytical, and creative thinker with passion for quality.
- - Exceptional analytical and problem solving skills
- - Experience executing and contributing to automation infrastructure.
- - Prototyping and tools development is a plus
- - Programming skills in Scala, Python, Java or similar language is a plus
- - Experience in crafting and developing testing infrastructure for Distributed Systems, Big Data Platforms is a plus
- - Familiarity with Cassandra, Kafka, Spark, Hive and other big data tools is a plus
- - Hands-on testing on devices is a plus
As part of this team, you will establish, implement and evolve the formal QA processes to ensure that the group is using industry accepted standard methodologies. Design and develop the testing infrastructure i.e. testing tools, test frameworks , test reporting mechanisms to test the software, services, Alternative data platforms of the team as well as the existing and new machine learning models build on the platform. Integrate the testing infrastructure with the continuous integration and continuous deployment systems to ensure all of the tools, services developed are properly tested and meet the quality goals. Write different types of tests i.e. Unit, Integration , Acceptance for existing and new projects so as to ensure bug free software is delivered which is as per the requirements. Stay knowledgeable of new testing tools and strategies and evaluate the technologies to incorporate into the projects.