AIML - Machine Learning Engineer, Answers Information; AKI

AIML - Staff Machine Learning Engineer, Answers, Knowledge & Information (AKI)

Santa Clara, California, United States Machine Learning and AI

The Siri and Information Intelligence team is revolutionizing the way hundreds of millions of people access information on their devices, all while keeping user privacy at the forefront. As an Applied ML team, we’re pushing the boundaries of Apple Intelligence, result ranking, and innovative search technologies, all while running a low latency production service. Our work fuels intuitive information experiences across some of Apple’s most iconic products, including Siri, Spotlight, Safari, Messages, Lookup, and more.

Join us in shaping the future of how the world connects with information!

We are looking for a senior Machine Learning Engineer with a passion for using machine learning to build intelligent search applications. Our team researches and implements novel query understanding, ranking and response generation techniques, machine learning algorithms and models that power amazing Search experiences across Apple products.

In this role you will have the opportunity to develop LLMs and other NLP models for user productivity and improving Siri’s ability to answer personal domain questions. Our team owns models which are responsible for answering users’ questions using their personal documents with privacy at the forefront, and that integrates with other Siri capabilities to enable powerful user experiences. Role responsibilities include:

• Contribute to research, design, implementation, and evaluation of models to enhance quality and performance, and to support key functions for Personal Q&A.
• Implement and extend LLM models with fine‑tuning and RLXF methodologies. Develop high‑quality data pipelines to support these methodologies.
• Establish target quality metrics and evaluation sets for the team to track and improve.
• Design novel experiments to validate/refute hypotheses and support team‑wide decision making.
• Collaborate with partner teams to define product requirements and priorities, and to explore opportunities for enhancements to the Personal Q&A stack.
• Develop long‑term technical vision for Personal Q&A quality; identify problem areas and integrate solutions as part of a larger roadmap.

• 8+ years industry experience in Machine Learning, NLP and applying these techniques at scale
• Strong software engineering skills in mainstream programming languages, such as Python, Go, C/C++
• Bachelors in Computer Science

• In‑depth knowledge and expertise in training, evaluating, and applying Deep learning models, Large Language Models for production systems
• Extensive experience in building production ML systems and applications in search, recommendation systems, or information retrieval
• Ability to quickly prototype ideas / solutions, and perform critical analysis
• Background in search relevance and ranking, Q&A, personalization, user behavior/response modeling, or data‑driven decision‑making
• Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, or related field, or equivalent industry work experience

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 $184,700 and $324,800, 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…