Machine Learning Engineer, Siri Attention & Invocation
Apple
Machine Learning Engineer, Siri Attention & Invocation
Job Description
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something. “Hey Siri, let’s work together at Apple!" The Siri Attention & Invocation team is looking for Machine Learning Engineers passionate about enabling personalized 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 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 — just by saying ‘(Hey) Siri.’ 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 Siri Attention & Invocation, we own our user journeys end-to-end. We measure the impact of our deployed models not just on pre-ship evaluation sets, but also post-ship on production traffic. We optimize error rates on existing data. We also define new metrics that take into account the user experience we want to deliver 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 understand, personalize, and interact in new and exciting ways, then we cannot wait to hear from you.
Locations
- Seattle, Washington, United States 98117
Salary
Estimated Salary Rangemedium confidence
25,000,000 - 60,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learningintermediate
- model trainingintermediate
- model evaluationintermediate
- end-to-end pipelinesintermediate
- speaker recognitionintermediate
- deploying on-device modelsintermediate
- applied machine learningintermediate
- building modelsintermediate
- deploying modelsintermediate
- optimizing error ratesintermediate
- defining metricsintermediate
- on-device computationintermediate
- innovationintermediate
- collaborating with cross-functional teamsintermediate
- academic rigorintermediate
- engineering efficacyintermediate
- staying up-to-date with research advancementsintermediate
- delivering reliable modelsintermediate
- delivering robust modelsintermediate
Required Qualifications
- 5+ years of post-baccalaureate or equivalent experience with the following: (experience, 5 years)
- Strong background in machine learning and deep learning; experience in speech, speaker, and/or language recognition a plus, but not required (experience)
- Solid foundation in machine learning fundamentals, such as classification, feature engineering, clustering, semi-supervised learning, and domain adaptation (experience)
- 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, automating, and scaling end-to-end systems globally (e.g., PySpark, Airflow) (experience)
- Strong attention to detail, along with the analytical skills and the willingness to dive into data to explain anomalies and conduct error/deviation analyses (e.g., Jupyter) (experience)
- Outstanding problem solving, critical thinking, creativity, and interpersonal skills; ability to communicate effectively with engineers, scientists, managers, and cross-functional partners (experience)
Preferred Qualifications
- Master’s or Ph.D. degree in electrical engineering, computer science, machine learning, language technology, or related fields; outstanding candidates with Bachelor’s degrees and multiple years of significant engineering/product experience will also be considered (experience)
Responsibilities
- 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 Siri Attention & Invocation, we own our user journeys end-to-end. We measure the impact of our deployed models not just on pre-ship evaluation sets, but also post-ship on production traffic. We optimize error rates on existing data. We also define new metrics that take into account the user experience we want to deliver 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 understand, personalize, and interact in new and exciting ways, then we cannot wait to hear from you.
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Machine Learning Engineer, Siri Attention & Invocation
Apple
Machine Learning Engineer, Siri Attention & Invocation
Job Description
Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other’s ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It’s the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you’ll do more than join something — you’ll add something. “Hey Siri, let’s work together at Apple!" The Siri Attention & Invocation team is looking for Machine Learning Engineers passionate about enabling personalized 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 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 — just by saying ‘(Hey) Siri.’ 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 Siri Attention & Invocation, we own our user journeys end-to-end. We measure the impact of our deployed models not just on pre-ship evaluation sets, but also post-ship on production traffic. We optimize error rates on existing data. We also define new metrics that take into account the user experience we want to deliver 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 understand, personalize, and interact in new and exciting ways, then we cannot wait to hear from you.
Locations
- Seattle, Washington, United States 98117
Salary
Estimated Salary Rangemedium confidence
25,000,000 - 60,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Machine Learningintermediate
- model trainingintermediate
- model evaluationintermediate
- end-to-end pipelinesintermediate
- speaker recognitionintermediate
- deploying on-device modelsintermediate
- applied machine learningintermediate
- building modelsintermediate
- deploying modelsintermediate
- optimizing error ratesintermediate
- defining metricsintermediate
- on-device computationintermediate
- innovationintermediate
- collaborating with cross-functional teamsintermediate
- academic rigorintermediate
- engineering efficacyintermediate
- staying up-to-date with research advancementsintermediate
- delivering reliable modelsintermediate
- delivering robust modelsintermediate
Required Qualifications
- 5+ years of post-baccalaureate or equivalent experience with the following: (experience, 5 years)
- Strong background in machine learning and deep learning; experience in speech, speaker, and/or language recognition a plus, but not required (experience)
- Solid foundation in machine learning fundamentals, such as classification, feature engineering, clustering, semi-supervised learning, and domain adaptation (experience)
- 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, automating, and scaling end-to-end systems globally (e.g., PySpark, Airflow) (experience)
- Strong attention to detail, along with the analytical skills and the willingness to dive into data to explain anomalies and conduct error/deviation analyses (e.g., Jupyter) (experience)
- Outstanding problem solving, critical thinking, creativity, and interpersonal skills; ability to communicate effectively with engineers, scientists, managers, and cross-functional partners (experience)
Preferred Qualifications
- Master’s or Ph.D. degree in electrical engineering, computer science, machine learning, language technology, or related fields; outstanding candidates with Bachelor’s degrees and multiple years of significant engineering/product experience will also be considered (experience)
Responsibilities
- 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 Siri Attention & Invocation, we own our user journeys end-to-end. We measure the impact of our deployed models not just on pre-ship evaluation sets, but also post-ship on production traffic. We optimize error rates on existing data. We also define new metrics that take into account the user experience we want to deliver 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 understand, personalize, and interact in new and exciting ways, then we cannot wait to hear from you.
Tags & Categories
Answer 10 quick questions to check your fit for Machine Learning Engineer, Siri Attention & Invocation @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs