Machine Learning Engineer, Software QA - Creativity Apps

Apple

About The Position

The Creativity Apps QA team is seeking a Software QA Engineer, Machine Learning to help ensure the quality of Apple’s iOS and macOS creativity applications. The role takes projects from defining evaluation strategy through evaluation scripting and automation, leading testing, triaging and driving issues to resolution, and verifying that high-quality models are integrated into app clients through rigorous testing methodologies. The position offers an opportunity to help shape products for Apple customers and requires a self-motivated engineer with strong technical, problem-solving, and communication skills who is comfortable working in a sophisticated environment. The engineer scripts and parses data, works closely with annotation operations, and analyzes annotations and test results to verify end-to-end customer features. The role also develops workflow projects, performs regression testing, files bugs, and collaborates with team members on requirements and suitable testing processes and methodologies. The engineer must manage priorities systematically, communicate progress and risks through regular status updates, make sound judgments amid ambiguity, and ramp up quickly on existing and new technologies.

Requirements

At least 5 years of industry experience, ideally in quality assurance with a prior focus in machine learning.
Strong comprehension of machine-learning algorithms and supervised and unsupervised modeling techniques.
Understanding of machine-learning mechanics, deep learning, computer vision, natural language processing, and generative AI.
Proficiency in Python and/or Swift, or comparable programming languages.
Experience preparing and collecting evaluation data and ensuring data quality.
Meticulous, analytical, methodical, and creative problem-solving skills, with a commitment to improving quality.
Prototyping and tools-development experience.
Strong presentation skills and ability to adapt technical presentations to different audiences.
Proficiency using 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 a similar field, combined with an understanding of SQA methodologies, machine learning, and software engineering experience.
Strong technical, problem-solving, and communication skills; ability to work comfortably with ambiguity and make critical judgments.
Ability to manage priorities systematically and communicate progress and risks.

Nice To Haves

Understanding of subjective and objective image and video quality evaluation and color science concepts.
Understanding of SQA methodologies and practices and software engineering experience.
Familiarity with iOS and macOS.

Responsibilities

Define evaluation strategies for machine-learning projects.
Develop evaluation scripts and automation.
Lead all stages of testing and triage issues through resolution.
Ensure models are integrated into app clients and meet quality expectations through rigorous testing.
Script and parse data, and work with the annotation operations team.
Analyze annotations and test results to ensure features work end-to-end for customers.
Develop workflow projects, conduct regression testing, and file bugs.
Collaborate with team members to develop requirements and identify appropriate testing implementations, processes, and methodologies.
Manage priorities and communicate progress and risks through regular status updates.
Ramp up quickly on existing and new technologies.