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A leading technology company in Cambridge is seeking researchers for their AIML - Machine Translation team. Ideal candidates will hold an M.S or PhD in Computer Science and have experience with machine learning technologies such as Tensorflow or PyTorch. Responsibilities include developing user-facing speech translation systems. Apple is committed to diversity and inclusion in their hiring process.
Cambridge, England, United Kingdom Machine Learning and AI
The AIML - Machine Translation team is looking for outstanding researchers/scientists to develop the next generation of speech to speech translation technology to allow our users to communicate across language barriers.
You will take part in the next revolution of confluence between machine translation and human-computer interaction. Build significant impact in shipping machine translation technology to real-world users. Enable our users to seamlessly communicate without language barriers or access content in a foreign language through intuitive interfaces. Address practical problems related to mainstream adoption of Machine Translation including core technology, learning from user feedback, error recovery and user-interface design. We are looking for people who have a deep real passion for technology and collaborate with a team of researchers, engineers and designers towards making it available in the hands of millions of dedicated customers. Responsibilities Conduct independent applied research in the area of speech to speech translation Design large-scale, user-facing speech translation systems
At Apple, we’re not all the same. And that’s our greatest strength. We draw on the differences in who we are, what we’ve experienced and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. As a registered Disability Confident employer, we will work with applicants to make any reasonable accommodations. Apple will consider for employment all qualified applicants with criminal backgrounds in a manner consistent with applicable law. Learn more