AIML - Software Engineer (Search), MLPT
Apple Inc
Zurich, Switzerland
Job posting number: #7289307 (Ref:apl-200574197)
Posted: October 21, 2024
Job Description
Summary
Do you want to make Siri and Apple products smarter for our users? Here in the Machine Learning Platform Technology & Infrastructure group we build 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. Siri’s universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages, Lookup, and more. As part of this group, you will work with one of the most exciting high performance computing environments on Apple’s search product, with petabytes of data, millions of queries per second, and have an opportunity to imagine and build products that delight our customers every single day.
Description
In this role working on search you will work at the intersection between quality and performance, optimizing the high performance components that serve our indexes for large amounts of traffic, working on retrieval infrastructure to improve relevance for users inside the constraints that come with a high throughput index serving infrastructure, designing and implementing retrieval augmented generation that is fed by our search systems.
The typical tasks encompass:
* Designing features and systems that enable to perform retrieval on large token and embeddings-based indexes
* Optimizing throughput of the queries, analyzing how to let ranking engineers improve the relevance within the latency and budget envelope
* Streamlining onboarding and experimentation experience to our search systems to empower other teams to more efficiently use our components and iterate faster on their relevance improvements
* Improving data structures and algorithms to reduce the cost of serving large indexes
The typical tasks encompass:
* Designing features and systems that enable to perform retrieval on large token and embeddings-based indexes
* Optimizing throughput of the queries, analyzing how to let ranking engineers improve the relevance within the latency and budget envelope
* Streamlining onboarding and experimentation experience to our search systems to empower other teams to more efficiently use our components and iterate faster on their relevance improvements
* Improving data structures and algorithms to reduce the cost of serving large indexes
Minimum Qualifications
- Experience with at least one of the following programming languages: Go, Java, Python, Scala, C/C++, or Rust.
- Strong background in computer science, particularly in algorithms and data structures.
- Exceptional interpersonal skills, with the ability to work independently and collaboratively within a team.
- Familiarity with microservices, multithreading, or related technologies is a plus.
Preferred Qualifications
- Experience with information retrieval and machine learning applied to search.
- Exposure to the challenges of scalable backend infrastructure and performance, including diagnosing, analyzing, and resolving issues using profiling, debugging, and tracing tools.
- Proficiency with distributed computing platforms and technologies, such as AWS, GCP, Kubernetes, MapReduce, or similar.
- Experience designing and implementing large-scale data pipelines, with a Bachelor's or Master’s degree in Computer Science/Engineering or equivalent experience.
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