Job Overview:
At Apple, you will design, develop, and deploy large-scale services and platforms, focusing on improving speech technologies through machine learning. You’ll collaborate with teams across Apple to build intelligent applications, working at the intersection of speech recognition, natural language processing, multi-modal systems, TTS dialogue management, acoustic modeling, and language modeling. The role requires a strong machine learning background in speech/language processing, deep learning expertise, and software engineering skills in C++, Java, or Python, along with experience with deep learning toolkits like TensorFlow or PyTorch. A PhD, MS, or BS in Machine Learning, Computer Science, or related fields is required, and you should be creative, enthusiastic, and ready to work hands-on with multiple teams to turn research prototypes into production-quality implementations.
>> View full job details on Apple’s official website.
Resume and Interview Tips:
When tailoring your resume for the Speech Scientist/Engineer position at Apple, focus on highlighting your machine learning expertise in speech and language processing, as well as your hands-on experience with deep learning. Emphasize specific projects where you applied these skills, especially those involving speech recognition, natural language processing, or related technologies. Be sure to detail your software engineering abilities, particularly in C++, Java, or Python, and mention any experience with deep learning frameworks like TensorFlow or PyTorch. If you have worked on speaker recognition or similar technologies, make this a standout feature of your resume. Given Apple’s emphasis on turning research into production, showcase any experience you have in transitioning prototypes to real-world applications. Quantify your achievements where possible, such as performance improvements in models or scalability enhancements in deployed systems. Your education should be clearly listed, especially if you have a PhD or MS in Machine Learning or Computer Science, as this is a key qualification for the role.
For the interview, prepare to discuss your machine learning and deep learning expertise in depth, particularly as it applies to speech and language processing. Be ready to explain your approach to solving complex problems in these areas, and have examples of past projects ready to share. Expect technical questions that test your knowledge of speech recognition, natural language processing, and deep learning frameworks. You might also be asked to demonstrate your software engineering skills, so review your proficiency in C++, Java, or Python. Apple values collaboration, so be prepared to discuss how you’ve worked with cross-functional teams in the past and how you handle communication and teamwork. Since the role involves turning research into production, think about how you’ve bridged the gap between theory and practice in your previous work. Finally, show your passion for exploring new technologies and use cases, as this is a key trait Apple is looking for. Dress professionally but remember that Apple’s culture leans towards smart casual, so aim for a polished yet approachable look.