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Apple

Machine Learning Algorithm Validation Engineer

Apple, Cupertino, CA, United States


Machine Learning Algorithm Validation Engineer

Cupertino, California, United States

Hardware

Would you like to work on a dynamic team that is all about delivering an Apple-quality experience on some of the world’s most creative products? We are the Product Systems Quality team, and we are looking for a highly motivated, energetic, and experienced Algorithm Validation Engineer with a passion for delivering robust, inclusive, and state-of-the-art Computer Vision and Machine Learning algorithms in Apple’s next generation of products. You'll enjoy working on a team of QA engineers with diverse backgrounds as we refine the models that power Apple’s trademark simple and elegant user experience. Come be a part of our team and use creativity and innovation to test features that our customers love!

Description

You will work closely with algorithm development teams to design and execute live test procedures, aggressor searches, user studies, and annotation pipelines to improve and influence ML algorithm performance and design. By focusing on end-to-end system performance, you will evaluate and represent the true customer experience while using a deep understanding of the various components within the models to test comprehensively and efficiently. You’ll also work with hardware and software engineering teams to consider the system design and external factors that influence model performance. You will be proud of your work through every step of the development cycle and will help make Apple products more flexible, reliable, and easy to use.

Minimum Qualifications

  1. Bachelor’s degree in CS/CE/EE and a minimum of 2 years relevant industry experience.
  2. Strong programming skills and hands-on experience with Python.
  3. Experience in testing products utilizing computer vision, computational photography, generative AI, machine learning, or related areas.
  4. Ability to communicate effectively and collaborate with partner teams.
  5. Committed to encouraging an open and inclusive work environment.

Key Qualifications

Preferred Qualifications

  1. Academic background in data science, machine learning, computer vision, and statistical data analysis.
  2. Experience with relevant ML frameworks (PyTorch, TensorFlow, or JAX).
  3. Experience with CoreML, Swift, and iOS/macOS machine learning development.
  4. Experience in data analysis and developing data visualizations & reporting with tools such as Tableau or Superset.
  5. Understanding of how to test and quantify performance of sensing technologies such as IMU, capacitive, environmental, light, motion, radar, optical, acoustic, and evaluate user impact and performance.

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 $136,300 and $248,700, 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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