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Consumer Electronics, Software, Services, Retail

Machine Learning Engineer, Software QA - Creativity Apps

San Diego, CAOnsiteFull TimePosted 2 months agoVisa sponsorship available

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Required skills

  • Machine Learning
  • Python
  • Swift
  • Software QA
  • evaluation strategy
  • evaluation scripting
  • automation
  • regression testing
  • bug filing
  • data quality

Nice to have

  • image quality evaluation
  • video quality evaluation
  • color science
  • iOS
  • macOS

Role summary

Apple's Creativity Apps QA team is seeking a Software QA Engineer with a Machine Learning focus to ensure the quality of iOS and macOS creativity applications. This role involves defining evaluation strategies, scripting and automating tests, leading testing phases, resolving issues, and ensuring high-quality models are integrated into client applications. Responsibilities include scripting, data parsing, analyzing test results, developing workflows, and collaborating with other teams on requirements and methodologies. The ideal candidate is self-motivated, technically proficient in Python/Swift, understands ML algorithms, and has experience with LLMs and Generative AI for model evaluation.

Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The Creativity Apps QA team is seeking a Software QA Engineer, Machine Learning to help us ensure that our iOS and macOS creativity applications are high-quality. We’re looking for an engineer to take projects from defining evaluation strategy, evaluation scripting and automation, leading all stages of testing, triaging and driving issues to resolution, and ensuring high quality models are integrated into our Apps' clients through rigorous testing methodologies. You will have the unique and rewarding opportunity to help shape upcoming products that will delight and inspire millions of Apple’s customers every day.

Description


This position requires a self-motivated individual with strong technical, problem solving and communication skills, and the willingness to work in a sophisticated environment. Responsibilities include scripting, parsing data, and working closely with the annotation operations team. Analyzing annotations and test results to ensure the features work end-to-end for customers. Developing and implementing workflow projects, regression testing, and bug filing. You will work closely with other team members to develop requirements, identify appropriate testing implementations processes, and methodologies. You should be able to be comfortable with ambiguity and make educated, critical judgments. You must be effective and systematic at managing priorities, and communicating progress as well as risk through regular status updates. Have a proven ability to ramp up quickly on both existing and new technologies.

Minimum Qualifications


At least 5 years industry experience ideally in quality assurance with a prior focus in Machine Learning. Strong comprehension of machine learning algorithms, supervised and unsupervised modeling techniques. Understand of the mechanics of machine learning, deep learning, computer vision, natural language processing, and generative AI. Proficient in Python and/or Swift or comparable languages. Preparing and collecting data for evaluation and ensuring data quality. Meticulous, analytical, methodical and creative problem solving ability with a commitment to driving quality forward. Detail-oriented, analytical, methodical and creative thinker committed to driving quality forward. Prototyping and tools development experience. Strong presentation skills and ability to adapt technical presentation to various audiences. Proficiency in utilizing LLMs and Generative AI frameworks to automate model evaluation processes, optimize test execution times, and improve evaluation accuracy and efficiency. Bachelor's degree in Computer Science, Data Science, Applied Mathematics or similar, combined with an understanding of SQA methodologies, machine learning and software engineering experience.

Preferred Qualifications


Understanding of subjective/objective image and video quality evaluation, and color science concepts is a strong plus. Understanding of SQA methodologies and practices, software engineering experience preferred. iOS and macOS familiarity.

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