AIML - Machine Learning Engineer, Answers, Knowledge & Intelligence (AKI)
3 Months ago • All levels • $143,100 PA - $264,200 PA
Research Development
Job Description
Redefining navigation and exploration for millions using devices. This role involves applying and improving deep learning models to understand queries, retrieve and rank documents, and provide useful answers. Responsibilities include analyzing metrics, designing and training deep learning models using PyTorch, understanding product requirements, building and deploying machine-learned models for search components like query understanding and relevance ranking, and developing large-scale indexing and ML data pipelines. The team values strong technical skills, product vision, and a passion for local experiences, with a diverse background in applied science, NLP, and distributed systems engineering.
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 applying and improving upon the latest deep learning models in order to understand queries, retrieve and rank documents, and return useful answers to users’ questions. We are looking for people with experience in information retrieval, 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 an extraordinary Maps experience in Siri and Spotlight.
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:
- Analyze search ranking and relevance metrics to identify requirements, diagnose issues, and uncover opportunities.
- Design and train deep learning models using PyTorch and proprietary frameworks.
- Understand product requirements and translate them into well-defined modeling problems and engineering tasks.
- Build, deploy, and iterate on machine-learned models for various search components including query understanding, semantic retrieval, and relevance ranking.
- Develop and maintain large-scale indexing and ML data pipelines that support high-throughput, low-latency serving environments.
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:
- Analyze search ranking and relevance metrics to identify requirements, diagnose issues, and uncover opportunities.
- Design and train deep learning models using PyTorch and proprietary frameworks.
- Understand product requirements and translate them into well-defined modeling problems and engineering tasks.
- Build, deploy, and iterate on machine-learned models for various search components including query understanding, semantic retrieval, and relevance ranking.
- Develop and maintain large-scale indexing and ML data pipelines that support high-throughput, low-latency serving environments.
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