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Apple AIML - Software Engineer Search MLPT Switzerland, Zurich, Zurich 551150434
18.11.2024
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Description
In this role working on eval infrastructure for search you will be helping on empowering 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 have 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 let 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 to perform 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 is 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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