AIML- Machine Learning Engineer, Machine Learning Platform & Infrastructure

Summary
At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.

Do you want to make Spotlight search, Foundation models, Siri and other Apple products smarter for our users? The Information Intelligence teams are building groundbreaking technology for algorithmic search, machine learning, natural language processing, and artificial intelligence. The features we build are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for. Our universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari

As part of this group, you will work with one of the most exciting high performance computing environments, with petabytes of data and have an opportunity to imagine and build products that delight our customers every single day.



Description
We are responsible for Search infrastructure at Apple. We design and build infrastructure to support features that empowers Spotlight and Siri users. We are responsible for the end to end ownership of our pipelines and services, from conception, to design, to implementation, to deployment, to operations. As a result, each one of us takes our responsibilities seriously, while having a lot of fun building the best services at scale we can. We have numerous latency sensitive services, jobs and pipelines that solve problems within Search infrastructure engineering. As part of this team you'll have the opportunity to work with large scale systems with trillions of rows and many petabytes of data.

Candidate who joins our team will be responsible for the following

* Drive the feature from inception to production launch that will help improve Search, Foundation models, Siri & other Apple products

* Work with cross functional teams & stakeholders to solve ambiguous problems

* Build software that improves experimentation and helps team make better decisions about what to try next

* Drive the team & organizational goals & OKRs

* Deliver artifacts, code with high quality

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