AIML - Senior ML Engineer - Siri & Information Intelligence
Apply NowCompany: Apple
Location: Santa Clara, CA 95051
Description:
Summary
Siri helps hundreds of millions of people find the information they are looking for. A critical part of that mission is helping them quickly find and discover local businesses, places of interest, and addresses. Users rely on us for relevant and easy access to local information like finding a favorite or romantic restaurant, business hours, nearby coffee shop addresses, and directions to prominent locations.
The Geo domain team is redefining how hundreds of millions of people use their devices to navigate and explore the physical world around them. We are part of a wider effort to power search across a variety of Apple products - including Siri, Spotlight, Safari, Messages, and more. As part of our team, you will be leveraging and improving upon the latest deep learning models in order to understand queries, rank documents, and find useful answers to users' questions. We are looking for people with experience in query understanding, machine learning and search ranking powered by sophisticated, high-performance data ingestion pipelines. You will join a team that combines strong technical skills, product vision, and a love of all things local to bring together the pieces needed to deliver a world-class Maps experience in Siri and Spotlight.
Description
As a member of our fast-paced group you'll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team includes a diversity of backgrounds from applied scientists with a focus in NLP to experienced distributed systems engineers. As such we are looking for candidates with applied machine learning experience and strong engineering skills.
The role will have the following responsibilities:
- Analyzing search ranking and relevance requirements issues and opportunities
- Utilizing PyTorch and proprietary tools for training deep learning models
- Understanding product requirements then translating them into modeling tasks and engineering tasks
- Building machine-learned models for query understanding and search ranking
- Develop and maintain large scale indexing and ML data pipelines
Siri helps hundreds of millions of people find the information they are looking for. A critical part of that mission is helping them quickly find and discover local businesses, places of interest, and addresses. Users rely on us for relevant and easy access to local information like finding a favorite or romantic restaurant, business hours, nearby coffee shop addresses, and directions to prominent locations.
The Geo domain team is redefining how hundreds of millions of people use their devices to navigate and explore the physical world around them. We are part of a wider effort to power search across a variety of Apple products - including Siri, Spotlight, Safari, Messages, and more. As part of our team, you will be leveraging and improving upon the latest deep learning models in order to understand queries, rank documents, and find useful answers to users' questions. We are looking for people with experience in query understanding, machine learning and search ranking powered by sophisticated, high-performance data ingestion pipelines. You will join a team that combines strong technical skills, product vision, and a love of all things local to bring together the pieces needed to deliver a world-class Maps experience in Siri and Spotlight.
Description
As a member of our fast-paced group you'll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team includes a diversity of backgrounds from applied scientists with a focus in NLP to experienced distributed systems engineers. As such we are looking for candidates with applied machine learning experience and strong engineering skills.
The role will have the following responsibilities:
- Analyzing search ranking and relevance requirements issues and opportunities
- Utilizing PyTorch and proprietary tools for training deep learning models
- Understanding product requirements then translating them into modeling tasks and engineering tasks
- Building machine-learned models for query understanding and search ranking
- Develop and maintain large scale indexing and ML data pipelines