Machine Learning Engineer, Siri Attention & Invocation
Machine Learning Engineer, Siri Attention & Invocation
Posted on :
02-08-2025
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1 Vacancy
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Job 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 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 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.
- 5 years of post-baccalaureate or equivalent experience with the following:
- Strong background in machine learning and deep learning; experience in speech speaker and/or language recognition a plus but not required
- Solid foundation in machine learning fundamentals such as classification feature engineering clustering semi-supervised learning and domain adaptation
- 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)
- 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)
- Outstanding problem solving critical thinking creativity and interpersonal skills; ability to communicate effectively with engineers scientists managers and cross-functional partners
- Masters or Ph.D. degree in electrical engineering computer science machine learning language technology or related fields; outstanding candidates with Bachelors degrees and multiple years of significant engineering/product experience will also be considered
Employment Type
Full Time
Key Skills
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