Internship - Machine Translation Quality Estimation & Metrics

Vor 2 Tagen


Munich, Bayern, Deutschland Apple Vollzeit
Application Deadline: Friday 21st November

As part of Apple's Machine Learning and AI team, we transform every Apple product and because we fully integrate hardware and software, we can collaborate to deliver amazing experiences while protecting user data. We are offering an amazing internship opportunity to work directly with our R&D team in Munich on a machine translation problem. Collaborate with some of the best in the business and see how we build the world's most innovative products and experiences.

Description
Our aim is to create an experience that allows you to learn without pressure, gain practical skills, build real world experience, develop a greater understanding of our industry and form valuable connections. You will join an extraordinary team, including world-class software engineers and leading machine learning practitioners who are all passionate about applying groundbreaking techniques to AI. We will partner you with a dedicated mentor who is an authority in your specialist area. You and your mentor will collaborate to design and implement an innovative solution for a machine learning problem with particular focus on speech translation and machine translation. At the end of your internship, you will have the chance to present your work to the AIML leadership. Where appropriate, there may be the opportunity to submit your work for publication at a suitable conference.

Minimum Qualifications
Enrolled as a student on a Master's, PhD or equivalent program
In-depth knowledge in deep learning (DL) and statistical machine learning (ML)
Experience with quality estimation and evaluation metrics for machine translation
Strong publication record demonstrating innovative research
Strong programming skills in Python and knowledge of common ML frameworks (e.g. PyTorch)

Preferred Qualifications
Able to deliver ML technologies aligned with the core values of Apple, ensuring the highest standards of quality, scientific rigour, innovation, and respect for user privacy
Expertise in one or more of the following fields: quality estimation, evaluation metrics, machine translation and natural language processing

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