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Consumer Electronics, Software, Services, Retail

Machine Learning Engineer, Evaluation, Agentic Search Capabilities

Cupertino, CAOnsiteFull TimePosted 28 days agoVisa sponsorship available

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Required skills

  • Machine Learning
  • ML evaluation systems
  • Python
  • C/C++
  • prototyping
  • critical analysis
  • communication skills
  • partner teams
  • Statistics

Nice to have

  • production ML systems
  • search
  • NLP
  • recommendation systems
  • information retrieval
  • data collection

Role summary

The Agentic Search team is seeking a senior Machine Learning Engineer to evaluate personalized agentic search applications, impacting experiences across Siri, Spotlight, Mail, and Messages. You will focus on advancing Apple Intelligence by building scalable systems for data generation, quality assessment, and developing offline/online metrics for search and model quality. This role requires strong software engineering skills in Python and C/C++, with a minimum of 6 years of experience in building ML evaluation systems at scale. Preferred experience includes production ML systems in search, NLP, or recommendation systems, and expertise in data quality assessment and metrics development.

The Agentic Search team is redefining how hundreds of millions of people access information across Apple devices, with privacy built in from the ground up. As part of the Agentic Search Evaluation team, you will help advance Apple Intelligence through personalized search that powers experiences across Siri, Spotlight, Mail, Messages, and more. Your team researches and builds deep search systems for Personal Question Answering, enabling Siri to answer questions about a user's emails, messages, events, files, and more, while keeping personal data private.

Description


We are looking for a senior Machine Learning Engineer with a passion for building scalable, high quality solutions to evaluate personalized agentic search applications. In this role, you will directly impact how we assess and improve the quality of novel agentic search applications by driving solutions for data generation, data quality assessment, offline and online metrics, and methods for statistical model and search quality assessment. Your work will impact the quality of innovative Personalized Agentic Search experiences across Siri and Apple products. In this role you will have the opportunity to build scalable systems for comprehensive evaluation of personalized model and search systems, develop data generation and curation methodologies to support evaluations, and design online and offline metrics for product quality assessment. Our team is responsible for models and evaluation of search experiences that answer user’s questions using their personal documents with privacy at the forefront.

Minimum Qualifications


6+ years industry experience in building Machine Learning or ML evaluation systems at scale. Strong software engineering skills in mainstream programming languages, such as: Python, C/C++. Ability to quickly prototype ideas and solutions, and perform critical analysis. Strong communication skills and ability to drive solutions in collaboration with partner teams. Bachelors in Computer Science, Engineering, Statistics or related field.

Preferred Qualifications


Experience in design and building production ML systems and applications in search, NLP, recommendation systems, or information retrieval. Experience in data collection, data generation and/or data quality assessment of language, image or multi-modal data. Strong skills for quality metrics development; interpretation of evaluations; and presentation to executive audience. Advanced degree (Master’s or Ph.D.) in Computer Science, Engineering, Statistics, or related field, or equivalent industry work experience.

Sample Apple interview questions

  • 1

    Design a typeahead box for a search engine

    system designmedium
  • 2

    Design a rate limiter

    system designmedium
  • 3

    Architect a key-value store for distributed systems.

    system designmedium
  • 4

    Design a system to schedule jobs in a distributed environment

    system designmedium
  • 5

    What is an API and how does it work?

    technicalmedium

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