Machine Learning Engineer

Cupertino, California, United States

Apple

We’re a diverse collective of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways.

View all jobs at Apple

Summary

Posted: Oct 11, 2024
Weekly Hours: 40
Role Number:200573153

The Applied Sensing & Health team has built innovative ways for users to improve their health and fitness. When you exercise and move with your devices, it’s the sensor fusion algorithms from the engineers and scientists on this team, that track human motion and provide interpretable insights. Join us to work with people who have expertise and passion to model human movement and have a positive impact in users’ lives. As a member of our dynamic group, you will have the unique and rewarding opportunity to shape upcoming products that will delight and inspire millions of Apple’s customers every single day.

Description


The Applied Sensing & Health team delivers Health and Fitness features for Apple Watch, iPhones and other Apple products. We are looking for ML engineers who care deeply about their craft to join us. The roles and responsibilities include scoping, designing and implementing models for Health and Fitness algorithms, optimizing implementations for power, memory and performance, and coordinating closely with multi-disciplinary teams across the company. You will work with scientists, engineers, QA, and project managers throughout the software lifecycle in successfully delivering best-in-class secure and scalable systems. Most importantly, you will help ship features that impact millions of users on a daily basis.

Minimum Qualifications


  • MS 5+ years experience in quantitative data science discipline (statistics/biostatistics, epidemiology, computer science).
  • Strong background in developing machine learning and/or deep learning models, preferably with time series data.
  • Strong proficiency in Python and ML frameworks e.g. PyTorch, Tensorflow


Preferred Qualifications


  • Ph.D or 5+ years experience in quantitative data science discipline (statistics/biostatistics, epidemiology, computer science).
  • You can form hypotheses, and can creatively apply different statistical approaches to the data in proving the hypotheses.
  • You appreciate the computational and storage complexities that come with modeling using large datasets.
  • You leverage distributed compute/storage models when the scale of data calls for it.
  • You believe that the integrity of the tooling and pipelines are critical to coming up with high quality analyses.
  • You understand the role feedback plays in your growth, and how effective communication affords more feedback opportunities.


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. 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.



  • 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.




Job stats:  15  3  0

Tags: Biostatistics Computer Science Deep Learning Machine Learning Pipelines Python PyTorch Statistics TensorFlow

Perks/benefits: Career development Equity / stock options Fitness / gym Health care Relocation support Startup environment

Region: North America
Country: United States

More jobs like this