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AIML - Staff Machine Learning Engineer, Siri and Information Intelligence

Apple
Santa Clara, United Statesfull_timeVerifiedPosted 17 Mar 2025
💰 $378,700/yr($207,800/yr$378,700/yr)

About the role

Summary

Posted: Mar 17, 2025

Role Number:200593653

Do you want to make Siri and Apple products smarter for our users? The Siri and Information Intelligence team is redefining how hundreds of millions of people use their devices to get information. We are an Applied ML team pushing the limits of question answering, assistant response ranking, summarization, and search technologies, while also responsible for a production service. We are part of a wider effort to power information across a variety of Apple products – including Siri, Spotlight, Safari, Messages, Lookup, and more. As part of our team, you will be leveraging and improving upon the latest deep learning techniques, such as LLM and RAG, in order to understand queries and user intents, rank documents, and find useful answers to users’ questions. Our team is responsible for training, fine-tuning and deploying these models at scale, using the latest advances for online inference optimization.

Description


As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team includes a diversity of backgrounds from applied scientists with a focus in NLP to experienced distributed systems engineers. As such, we are looking for candidates with in-depth understanding of machine learning fundamentals, applied machine learning experience, and strong software engineering skills.

Minimum Qualifications


  • Experience in the following:
  • Understanding product requirements then translating them into modeling and engineering tasks
  • Analyzing search ranking and relevance requirements, issues, and opportunities
  • Utilizing PyTorch, TensorFlow, or JAX for training and deploying deep learning models
  • Building ML models for retrieval, relevance ranking, or query understanding
  • MS in Computer Science or related field
  • 10 years of work experience in machine learning, deep learning or related field


Preferred Qualifications


  • PhD in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field
  • Strong industry background and experience in search and related technologies (LLMs, Machine Learning, NLP, Information Retrieval, Question Answering)
  • Strong and validated experience of ML development and production systems
  • Experience working with foundation models and LLMs


Pay & Benefits


  • At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $207,800 and $378,700, and your base pay will depend on your skills, qualifications, experience, and location.

    Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

    Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.



  • Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, colo

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Company

Apple

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