Machine Learning Engineer, Apple Search & Knowledge Platforms

Apple Inc.; Seattle (WA); On-site; USD 139,500 - 258,100; Full time

Benefits offered by this job

Comprehensive medical and dental coverage

Tuition reimbursement for formal education

Employee stock purchase plan

Job summary

Apple Inc. in Seattle is looking for a Machine Learning Engineer for its Knowledge Quality Team. You will develop advanced machine learning solutions that power applications like Siri and Spotlight, working with extensive data sets and cutting-edge technology.

The role requires strong programming abilities in languages like Python and Scala, and experience with machine learning frameworks including PyTorch. Apple offers comprehensive benefits, including stock options and educational reimbursement.

Qualifications

• Excellent programming skills in mainstream programming languages such as Python, Scala, and Go.
• Prior experience with Machine Learning Frameworks such as PyTorch and TensorFlow.
• Working experience with NLP and Large Language Models.

Responsibilities

• Build state-of-the-art Gen AI components at scale for Siri.
• Design features for large-scale data management and knowledge extraction.
• Work with petabytes of data and millions of queries per second.

Skills

Programming skills in Python, Scala, and Go

Experience with PyTorch and TensorFlow

NLP and Large Language Models experience

Working with large data sets and Apache Spark

Problem-solving and analytical skills

Interpersonal and teamwork skills

Passion for product building

Education

PhD or Graduate degree in relevant field

Tools

Apache Spark

Job description

Machine Learning Engineer, Apple Search & Knowledge Platforms

Seattle, Washington, United States Machine Learning and AI

The Apple Knowledge Quality Team is building the next-generation of machine learning solutions for Knowledge Q&A at Apple and help power features including Siri and Spotlight. 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. As part of this group, you will work with one of the most exciting high performance computing environments, 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

The Knowledge Quality team is looking for extraordinary Machine Learning engineers to join a team of world-experts on Large-Scale Data Management and Machine Learning Systems. Together, you will be pushing the boundaries of Knowledge Question Answering in Siri. As part of the Knowledge Quality team, you will build state-of-the-art Gen AI components at scale to power question answering for Siri. You will design and develop features for a platform that touches upon large-scale data management, machine-learning systems over graph data, and knowledge extraction over semi-structured and unstructured data feeds. You will have the outstanding opportunity to change how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for.

Minimum Qualifications

• Excellent programming skills in mainstream programming languages such as Python, Scala, and Go
• Prior experience with Machine Learning Frameworks such as PyTorch and Tensorflow
• Working experience with NLP and Large Language Models
• Experience working with large data sets and pipelines, ideally using the Apache software stack (e.g. Spark)
• Broad knowledge of computer science and systems; ability to quickly learn new domains
• Excellent problem‑solving and analytic skills
• Good interpersonal skills and teamwork
• Passion for building phenomenal products and curiosity to learn

Preferred Qualifications

• PhD or Graduate degree with research/work experience in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field
• Experience in Natural Language Processing including RAG based Generative AI and transformer architecture

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 $139,500 and $258,100, 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 seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.