AIML - ML Research Engineer in Speech, Siri and Information Intelligence
Seattle, Washington
Summary
"Hey Siri, let's work together at Apple!" The Siri team is looking for Machine Learning Engineers passionate about enabling natural Siri interactions and delivering such technology to users on a global scale. Build end-to-end model training and evaluation pipelines. Push the envelope on the latest research developments in speech and speaker recognition. Deploy machine-learned, on-device models that are aligned with the core values of Apple, ensuring the highest standards of quality, innovation, and respect for user privacy. And work with the people who created the intelligent assistant that helps millions of people around the world get things done through natural interactions with Siri. You should be creative, hard working, and ready to communicate and collaborate with multiple teams.
Key Qualifications
Strong coding skills in Python, C/C++; Comfortable with frequent, incremental code testing and deployment
Strong background in applied machine learning and deep learning; experience in speech, speaker, and/or language recognition a plus
Proficiency in deep learning / machine learning frameworks (e.g., PyTorch, TensorFlow) and scripting languages (e.g., Python, bash), with strong software engineering fundamentals and an interest in optimizing and scaling systems globally
Demonstrated strength in handling technical uncertainty and collaborating with partner teams to solve complex machine learning modeling problems
Description
You will be part of a team whose focus is on applied machine learning, on building and deploying models that constantly advance the state-of-the-art. But that is only half the story! In our team, we own products and user experiences end-to-end. We measure the impact of our deployed models not just on offline test sets, but also on production traffic. We optimize error rates on existing data. We also define new metrics and apply them to the data that best represents the next feature we ship. And we are sometimes constrained by the limits of on-device computation - that is where your ability to innovate will be most impactful. You will collaborate with many dynamic, cross-functional teams consisting of software engineers and machine learning engineers/scientists. The ideal candidate will excel in both academic rigor and engineering efficacy, staying up-to-date with the latest research advancements as well as delivering reliable and robust models to all devices for all users around the world. If you are passionate about building outstanding products and using the full spectrum of your skills to extend the core technology that lets Siri, personalize, and interact in new and exciting ways, then we cannot wait to hear from you.
Education & Experience
Ph. D. in a Machine Learning or related field, or M.S. with 3+ experiences in the area of Speech/Language Processing or Machine Learning
"Hey Siri, let's work together at Apple!" The Siri team is looking for Machine Learning Engineers passionate about enabling natural Siri interactions and delivering such technology to users on a global scale. Build end-to-end model training and evaluation pipelines. Push the envelope on the latest research developments in speech and speaker recognition. Deploy machine-learned, on-device models that are aligned with the core values of Apple, ensuring the highest standards of quality, innovation, and respect for user privacy. And work with the people who created the intelligent assistant that helps millions of people around the world get things done through natural interactions with Siri. You should be creative, hard working, and ready to communicate and collaborate with multiple teams.
Key Qualifications
Strong coding skills in Python, C/C++; Comfortable with frequent, incremental code testing and deployment
Strong background in applied machine learning and deep learning; experience in speech, speaker, and/or language recognition a plus
Proficiency in deep learning / machine learning frameworks (e.g., PyTorch, TensorFlow) and scripting languages (e.g., Python, bash), with strong software engineering fundamentals and an interest in optimizing and scaling systems globally
Demonstrated strength in handling technical uncertainty and collaborating with partner teams to solve complex machine learning modeling problems
Description
You will be part of a team whose focus is on applied machine learning, on building and deploying models that constantly advance the state-of-the-art. But that is only half the story! In our team, we own products and user experiences end-to-end. We measure the impact of our deployed models not just on offline test sets, but also on production traffic. We optimize error rates on existing data. We also define new metrics and apply them to the data that best represents the next feature we ship. And we are sometimes constrained by the limits of on-device computation - that is where your ability to innovate will be most impactful. You will collaborate with many dynamic, cross-functional teams consisting of software engineers and machine learning engineers/scientists. The ideal candidate will excel in both academic rigor and engineering efficacy, staying up-to-date with the latest research advancements as well as delivering reliable and robust models to all devices for all users around the world. If you are passionate about building outstanding products and using the full spectrum of your skills to extend the core technology that lets Siri, personalize, and interact in new and exciting ways, then we cannot wait to hear from you.
Education & Experience
Ph. D. in a Machine Learning or related field, or M.S. with 3+ experiences in the area of Speech/Language Processing or Machine Learning
Created: 2024-05-07
Reference: 200474372
Country: United States
State: Washington
City: Seattle
ZIP: 98109
About Apple
Founded in: 1976
Number of Employees: 154000
Website: https://www.apple.com/
Career site: https://www.apple.com/careers/us/
Wikipedia: https://en.wikipedia.org/wiki/Apple_Inc.
Instagram: https://www.instagram.com/apple/
LinkedIn: https://www.linkedin.com/company/apple
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