HomeKit Machine Learning Engineer

The HomeKit team provides the foundation which enables an entire ecosystem of

secure and intelligent connected home devices. Our mission is to create a

scalable, distributed system that will transform how people interact with their

home accessories. We are looking for a dedicated and passionate engineer to help

advance our Home platform intelligence and elevate it to new heights. As a

Machine Learning Engineer you will have an opportunity to be part of Smart Home

focused ML innovation within Apple, initially focused on Applied ML for Computer

Vision. The team 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.

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

MINIMUM QUALIFICATIONS

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

related field. A strong curiosity, willingness to dive deep into unfamiliar

problems, and an eagerness to learn and grow in a fast-evolving field.

Proficient in Python and deep learning frameworks like PyTorch, as well as

familiarity with a language like Swift, C, C++ or Objective C.

PREFERRED QUALIFICATIONS

Experience with training ML models including deep learning based models and

model optimization. Able to define metrics, evaluate ML models, and perform

error analysis. Familiar with recent advances in deep learning.