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Apple

AIML - Machine Learning Engineer, MIND

Cupertino, CA

Summary

Posted: May 8, 2024

Weekly Hours: 40

Role Number:200538597

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you will have an opportunity to be part of an ML innovation organization within Apple that has its roots in the computer vision research community. MI is well positioned for strategic contributions in the short-term (on well-known Apple products) and in the long-term (on highly ambitious, high-risk, high-reward projects). This role has a strong focus on shipping ML-based features and products. You'll innovate in the entire end-to-end ML production pipeline. This includes but is not limited to crafting creative approaches to datasets, model training, and on-device inference optimizations. Our ideal team member is fearless when it comes to trying new things and is willing to iterate on ideas. We value team members who can quickly prototype, iterating all the way to high-quality implementations.

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Description

As a member of this team, you will use your background to: - Develop features and models to improve the capabilities of systems that use machine learning - Scale up model training, build data pipelines, and tuning to improve system performance - Review and implement pioneering machine learning algorithms - Build software that improves rate of experimentation We prefer candidates with the following optional qualifications - Experience with modeling vision problems in the areas of object detection, facial recognition, and/or temporal machine learning - Experience with building efficient ML models through HW/SW co-design - Experience crafting and defining datasets and metrics for novel tasks - Experience with shipping ML features and products

Minimum Qualifications

Minimum Qualifications

Key Qualifications

  • Proficient in Python and deep learning frameworks like PyTorch
  • Experience with training ML models including deep learning based models
  • Able to define metrics, evaluate ML models, and perform error analysis
  • Familiar with recent advances in deep learning

Preferred Qualifications

Preferred Qualifications

Education & Experience

Bachelor's, Master's, or PhD or equivalent experience in Computer Science or a related field

Additional Requirements

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 $138,900 and $208,300, 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. Learn more about Apple Benefits.

    Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

More

  • 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. Learn more about your EEO rights as an applicant.

Client-provided location(s): Cupertino, CA, USA
Job ID: apple-200538597
Employment Type: Other

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