Machine Learning Engineer, Software QA - Creativity Apps

Job summary

You will lead the evaluation strategy, scripting, and automation for machine learning models within iOS and macOS creativity applications. This role involves collaborating with annotation teams to analyze test results and ensure high-quality, end-to-end feature performance.

Job details

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.

What you’ll do

You will lead the evaluation strategy, scripting, and automation for machine learning models within iOS and macOS creativity applications. This role involves collaborating with annotation teams to analyze test results and ensure high-quality, end-to-end feature performance.

Requirements

Candidates must have at least 5 years of industry experience in quality assurance with a focus on machine learning and proficiency in Python or Swift. A bachelor's degree in Computer Science, Data Science, or a related field is required, along with strong analytical and problem-solving skills.

Listed skills

• Machine learning · Preferred
• Python · Preferred
• Swift · Preferred
• Data analysis · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Machine Learning
• Software QA
• Python
• Swift
• Deep Learning
• Computer Vision
• Natural Language Processing
• Generative AI
• LLMs
• Automation
• Data Analysis
• Regression Testing
• Bug Filing
• Prototyping
• Model Evaluation
• SQA Methodologies
• Technical Presentations
• Generative Artificial Intelligence
• Workflow Management
• Self-Motivation
• Apple IOS
• Mac OS
• Applied Mathematics
• Communication
• Computer Science
• Creativity
• Creative Problem Solving
• Data Collection
• Data Quality
• Problem Solving
• Python (Programming Language)
• Machine Learning Algorithms
• Mechanics
• Natural Language Processing (NLP)
• Operations
• Parsing
• Presentations
• Quality Assurance
• Safety Assurance
• Software Engineering
• Software Quality (SQA/SQC)
• Test Execution Engine
• Evaluation Strategy
• Scripting
• Filing
• Prioritization
• Data Science
• Detail Oriented
• Swift (Programming Language)

Job areas

• Technology
• Software
• Engineering
• Data & Analytics
• Creative & Media
• Machine Learning Software Engineer
• Software QA Engineer / Tester
• Software and Applications Developers and Analysts Not Elsewhere Classified
• Software Quality Assurance Analysts and Testers

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