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Join the Siri team at Apple! Build and contribute to a product and company that that is building products, personal devices, and software designed to enrich people’s lives. Work on building and advancing the world’s most popular intelligent assistant that helps millions of people get things done - just by asking.
Global Siri works to take Siri to the next level of intelligence and capabilities in all languages and markets. We build machine learning models, systems, and software that understands the intents hundreds of millions of users and their billions of requests to Siri, on Apple devices such as iPhone, iPad, Apple Watch, Mac, AirPods, HomePod, Vision Pro and Apple TV. On the Global Scaling, Data, and Tools team, we work on ML modeling and algorithms, data platforms and technologies, and end-to-end ML product engineering to surprise and delight customers around the world in the languages that they speak.
Description
We seek a Senior Machine Learning Engineer / Tech Lead who is passionate about collaborating across teams in Siri and Apple to design, build, and deploy world-class machine learning systems that help Siri best serve the needs of our users. In this role, you will work on creating and improving the accuracy, speed, reliability, and capability of Global Siri’s models and systems. We are particularly interested in “full-stack” machine learning engineers with strong experience in research, software engineering, and have strong leadership potential.
You should be passionate about building outstanding products, and using the full spectrum of your skills to drive technical and organizational advancements. The ideal candidate is equally comfortable with the latest academic/research advancements in ML, LLMs, NLP, and related areas, diving into all parts of the full engineering/machine learning stack to diagnose user-facing issues and develop principled solutions, and deeply engaging in product metrics and goals with product managers, designers, and executives. Software engineering experience with both server-based and client-side (e.g. on-device) models is a definite asset. In this role, the ability to communicate complex technical ideas to diverse audiences, including research scientists, data scientists, engineers, designers, managers, and other stakeholders across Siri and Apple is also essential.
This position involves a wide variety of skills and innovation. In addition to your individual technical contributions, there are immense opportunities to multiply the impact those around you by mentoring, motivating and challenging engineers to deliver features at high quality. If you are looking for a role that is challenging, impactful, has immense growth opportunities, this role is for you.
Preferred Qualifications
Experience in data science and analytics, including data annotation, statistical analyses, A/B testing, and/or conducting experiments and investigations in large-scale usage data environments
Self-starter with a proven ability to handle multiple projects with strict deadlines
Experience in the iOS development ecosystem (e.g. Swift, Objective-C, CoreML, or SiriKit) is a plus
Experience in localization, internationalization, machine translation, or language technologies is an asset
Minimum Qualifications
Master's or PhD degree in computer science, software engineering, machine learning, language technologies, or related fields; outstanding candidates with Bachelor's degrees and multiple years years of significant engineering/product experience will also be considered
10+ years of experience developing, shipping, and measuring industry-scale machine learning-based software systems; experience working on large-scale NLU systems a strong asset.
Experience as a senior engineer, tech lead, or engineering manager for a machine learning-based product, including mentoring other engineers, working with program and product managers, and communicating accomplishments, metrics, and challenges to cross-functional stakeholders and leaders
Expertise and experience in Large Language Models (LLMs) or other foundation models, ideally demonstrated through publications or shipping foundation model-based features and products.
Strong background in machine learning, deep learning, and foundation models, as demonstrated through top-tier publications and/or successful development of training data, models, or software in commercial machine learning systems.
Excellent software engineering skills: Proficiency in at least one object-oriented language (e.g. Java, C++, Objective-C, or Swift), scripting languages (e.g. Python, Ruby, bash), and deep learning/machine learning frameworks (e.g. TensorFlow, PyTorch, or CoreML)
Outstanding problem solving, critical thinking, creativity, organizational, design, and interpersonal skills; ability to work with all levels of engineers, scientists, designers, and communicate effectively with management, leadership, and cross-functional partners
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 $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 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.