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 eval infrastructure for search, you will be helping to empower engineers working on relevance with their experimentation needs, letting them iterate more quickly on their ideas within the infrastructure that serves our large-scale indexes. For example, you would help them by designing end-to-end solutions that allow them to get insights into the impact their work has on the search quality, or enable them to evaluate with confidence the changes they make. The typical tasks encompass:
Designing and developing solutions to enable and orchestrate reliable data extraction and analysis at scale.
Developing and integrating experimentation-focused systems that accelerate the iterations with ML models against large indexes.
Building tooling that lets engineers conduct opportunity analysis and identify where they can bring value most.
Designing and implementing systems that integrate with our retrieval augmented generation and have insights into how these components behave.
Designing features and systems that enable retrieval on large token and embeddings-based indexes.
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.
Minimum Qualifications
Demonstrated experience with at least one of the following programming languages: Go, Java, Python, Scala, C/C++, Rust.
Strong background in computer science: algorithms and data structures.
Phenomenal interpersonal skills are required; able to work independently as well as in a team.
Preferred Qualifications
Bachelor's or Master’s degree in Computer Science/Engineering, or equivalent experience.
Experience with product ownership, driving conversations to understand and prioritize internal user needs and how to translate them to implementation.
Proficiency with distributed computing platform and technologies such as AWS, GCP, Kubernetes, MapReduce, or similar.
Exposure to the challenges of scalable backend infrastructure and performance and how to diagnose, analyze, and resolve them with knowledge of profiling, debugging, tracing tools.
Experience with information retrieval, ML applied to search, designing and implementing large-scale data pipelines.
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