Overview

We are looking for engineers with a passion for using machine learning to create intelligent applications. In this highly accomplished, deeply technical and close-knit team of data scientists and machine learning engineers, you will create tools that are used by millions of people. You will design and implement new machine learning algorithms and techniques and collaborate with the most innovative product development teams in the world. Our team builds the platform that enables teams across Apple to develop machine-learning solutions that power amazingly intelligent user experiences.
An example open source project our team released is CoreML: https://developer.apple.com/documentation/coreml which is a tool for IPhone application developer to quickly deploy ML applications on Apple devices.
We are looking for new energetic members to join our ML Applications team that collaborates with product teams on a variety of projects. In this role, you will have the opportunity to engage with every cool project around Apple, and use your data science, machine learning and artificial intelligence skills to solve some of the most challenging technical problems in the next generation of products that will delight millions of people.
Description
As a member of the ML Applications team, you will engage directly with data scientists and engineers in Apple product teams to co-develop machine learning solutions for a variety of tasks and projects using a variety of tools and techniques. You will also be a trusted advisor for best practice machine learning development. Your responsibilities include:
Co-developing machine learning solutions with data scientists and engineers on product teams
Developing proof-of-concept apps that use machine learning to demonstrate product feature feasibility
Providing technical guidance to product teams on the choice of machine learning approaches appropriate for a task
Providing architectural guidance on transitioning prototypes to high-performance production models
Providing feedback on tools and new features needed back to platform development teams

Company:

Apple

Qualifications:

Education Details
PhD in Machine learning, Statistics, Computer Science, Bioinformatics or related field or related field with 2+ years of machine learning industry experience,
or
MS in related field with 2+ years building machine learning models in industry
Key Qualifications
Minimum of 2 years experience applying machine learning techniques to build models that power products & experiences
Experienced user of machine learning and statistical-analysis libraries, such as GraphLab Create, scikit-learn, scipy, R, NetworkX, Spacy, and NLTK
Deep understanding of the algorithms and the ability to tweak algorithms when needed or implement new algorithms
Experience with deep learning frameworks, such as mxnet, Torch, Caffe, and TensorFlow is a plus
Strength in one of the following domains: deep learning, NLP, computer vision, recommenders, time series data
Strong Software Development Skills With Proficiency In Python Preferred

Educational level:

Master Degree

Level of experience (years):

Mid Career (2+ years of experience)

How to apply:

Please mention NLP People as a source when applying

https://jobs.apple.com/il/search?job=113019169&openJobId=113019169&board_id=17682#&openJobId=113019169

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About Apple

Apple reinvented the mobile phone with its revolutionary iPhone and App Store, defined the future of mobile media and computing devices with iPad and has announced Apple Watch, its most personal device ever. Apple leads the digital music revolution with its iPods and iTunes online store, continues the rapid pace of innovation of mobile software with iOS and integrated services including Apple Pay and iCloud. Apple designs Macs, the best personal computers in the world with OS X, and free iOS and OS X apps like iWork and iMovie.

Apple is an Equal Employment Opportunity Employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities.