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For Companies At a Glance
- Tasks: Join a team to develop and maintain machine learning products for Siri's speech recognition.
- Company: Be part of Apple, a leader in technology and innovation, impacting millions globally.
- Benefits: Enjoy a collaborative environment with opportunities for growth and cutting-edge projects.
- Why this job: Work on exciting challenges that enhance user experience and contribute to groundbreaking technology.
- Qualifications: Bachelor's, Master's, or Ph.D. in Computer Science or related field; 3+ years in machine learning.
- Other info: Apple values diversity and inclusion, ensuring equal opportunity for all applicants.
The predicted salary is between 43200 - 72000 £ per year.
AIML – Machine Learning Engineer, Siri Automatic Speech Recognition
Cambridge, Massachusetts, United States
Machine Learning and AI
We are looking for engineers passionate about using machine learning to build and maintain multiple machine learning products that power Siri. In this highly accomplished, deeply technical, and close-knit team of machine learning specialists, software engineers, and infrastructure experts, you will build products that are used by millions of people. You will have the opportunity to contribute to exciting projects around Apple and use your data science, machine learning, and analytical skills to tackle challenging technical problems and ship novel products that will delight our customers!
Description
You will be a part of a team that\’s responsible for a wide variety of speech-related development activities, including acoustic modeling, language modeling, model evaluations, text formatting, and tools development. Our speech recognition research is typically data-driven, and we are particularly excited about unsupervised and supervised techniques to leverage large quantities of data. You should be enthusiastic about building phenomenal products. Because you\’ll be working closely with researchers and engineers from a number of other teams at Apple, you\’re a standout colleague who thrives in a collaborative environment.
Minimum Qualifications
- Bachelors, Masters or Ph.D in Computer Science or Engineering or a related field, or equivalent experience
- 3+ years of experience in machine learning with focus on automatic speech recognition
- Proficiency in Python and SQL
- Strong problem-solving and data analytical skills
Preferred Qualifications
- Have contributed to shipping models/products to production
- Experience with foundation models
- Experience with large scale data processing
- Experience with Spark and machine learning frameworks like PyTorch
Additional Requirements
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.
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AIML - Machine Learning Engineer, Siri Automatic Speech Recognition employer: Apple Inc.
Contact Detail:
Apple Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AIML - Machine Learning Engineer, Siri Automatic Speech Recognition
✨Tip Number 1
Make sure to showcase your experience with automatic speech recognition in your conversations. Highlight specific projects where you've successfully implemented machine learning techniques, especially those that involved acoustic and language modeling.
✨Tip Number 2
Familiarize yourself with the latest advancements in foundation models and large-scale data processing. Being able to discuss recent trends and how they can be applied to Siri's development will set you apart during interviews.
✨Tip Number 3
Network with professionals in the field of machine learning and AI, particularly those who have experience with Apple or similar companies. Engaging in discussions about your shared interests can lead to valuable insights and potential referrals.
✨Tip Number 4
Prepare to demonstrate your problem-solving skills through practical examples. Be ready to tackle hypothetical scenarios related to speech recognition challenges, showcasing your analytical thinking and technical expertise.
We think you need these skills to ace AIML - Machine Learning Engineer, Siri Automatic Speech Recognition
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your experience in machine learning, especially in automatic speech recognition. Detail specific projects or products you've worked on that relate to the job description.
Showcase Technical Skills: Clearly list your proficiency in Python and SQL, as well as any experience with machine learning frameworks like PyTorch. Mention any relevant tools or technologies you have used in your previous roles.
Demonstrate Problem-Solving Abilities: Provide examples of how you've tackled complex technical problems in the past. Use metrics or outcomes to illustrate your impact and effectiveness in previous projects.
Express Enthusiasm for Collaboration: Since the role involves working closely with other teams, convey your ability to thrive in a collaborative environment. Share experiences where teamwork led to successful project outcomes.
How to prepare for a job interview at Apple Inc.
✨Show Your Passion for Machine Learning
Make sure to express your enthusiasm for machine learning and how it can be applied to real-world problems, especially in the context of speech recognition. Share specific examples of projects you've worked on that demonstrate your passion.
✨Highlight Collaborative Experiences
Since the role involves working closely with researchers and engineers, emphasize your experience in collaborative environments. Discuss how you’ve successfully worked in teams to tackle complex challenges and deliver results.
✨Demonstrate Technical Proficiency
Be prepared to discuss your technical skills in Python, SQL, and any relevant machine learning frameworks like PyTorch. You might be asked to solve a problem or explain your approach to a technical challenge, so brush up on your coding skills.
✨Prepare for Data-Driven Discussions
Given the data-driven nature of the role, be ready to talk about your experience with large-scale data processing and model evaluations. Bring examples of how you've used data to inform decisions and improve models in past projects.
