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Software QA Engineer, Machine Learning

at Apple
Compensation
$143k - $264k per year
Location
On-site
Travel Required?
No
Type
Full Time
Experience
Senior
Benefits
  • Equity
  • Tuition Assistance
  • Dental
  • Medical

Software QA Engineer, Machine Learning

Cupertino, California, United States
Software and Services

Summary

Posted:
Role Number:200566116
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 ML QA Engineer to help us ensure that our iOS and macOS creativity applications are high-quality. We’re looking for an engineer to take projects from initial data mining and research through all stages of prototyping, development and final integration into our Apps' clients. 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

  • Min. of 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.
  • Meticulous, analytical, methodical and creative problem solving ability with a commitment to driving quality forward.
  • Preparing and collecting data for evaluation and ensuring data quality.

Preferred Qualifications

  • Bachelor's degree combined with an understanding of SQA methodologies, machine learning and software engineering experience

Pay & Benefits

  • At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $143,100 and $264,200, and your base pay will depend on your skills, qualifications, experience, and location.Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.

Equal Opportunity Employer

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.

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