Machine Learning Engineer

Summary

Imagine what you could do with Machine Learning at Apple! Extraordinary ideas have a way of becoming excellent products, services, and customer experiences which are personalized, contextualized and intelligent to our users.

The ML Algo team at Apple works on various multidisciplinary ML projects related to Apple’s chip design technologies. We are looking for an outstanding machine learning engineer to develop state-of-the-art algorithms and infrastructure for the next generation of thoughtful and personal products we deliver. If you thrive at the intersection of algorithms, Apple’s outstanding chips and applied machine learning this position will excite and encourage you.

Key Qualifications

Independent, self-motivated and auto-didactic.

Proactive with proven creative and critical thinking capabilities

Strong theoretical and analytical skills

Hands-on DL development frameworks (PyTorch/TensorFlow)

Excellent verbal and written communication skills

Description

In this role you will join a team of researchers developing algorithms and technologies enabling the next generation of Apple products.

Core Responsibilities:

Research and develop ML algorithms in the fields of chip design

Bring to fruition proof of concept ideas to fully developed applications

Join forces and work with researchers from various Apple sites, collaborating with teams across Apple with multidisciplinary skills

Design and develop data pipelines for robust and scalable machine learning life cycle support

Develop processes and tools to analyze model performances

Education & Experience

M.Sc./P.h.D in Electrical Engineering/Computer Science with focus on machine learning

Additional Requirements

Apple is an equal opportunity employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants. Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities.

Role Number: 200495352