Machine Learning Engineer at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

05 Jan, 26

Salary

0.0

Posted On

07 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Deep Learning, Python, Statistics, Biostatistics, Epidemiology, Computer Science, Time Series Data, PyTorch, TensorFlow, Data Science, Modeling, Algorithm Design, Performance Optimization, Data Analysis, Feedback Communication

Industry

Computers and Electronics Manufacturing

Description

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 3+ 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.

Responsibilities

The role involves scoping, designing, and implementing models for Health and Fitness algorithms while optimizing implementations for power, memory, and performance. You will coordinate closely with multi-disciplinary teams to deliver secure and scalable systems.