Machine Learning Tools Engineer, Global Siri

Join the Siri team at Apple Build and contribute to a team and company 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 understand the intents of hundreds of millions of users and their billions of requests to Siri on Apple.. 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 are looking for a Machine Learning Tools Engineer who is passionate about collaborating across teams in Siri and Apple. Expect to design, build, and deploy extraordinary machine learning systems that help Siri best serve the needs of our users. You'll create and improve the accuracy and capability of Global Siri's models and systems. We are interested in "full-stack" machine learning engineers with strong experience in software engineering, research, and leadership potential.

Are you passionate about building outstanding products at the intersection of Machine Learning and Software Engineering? The ideal candidate has expertise in building scalable LLM-powered solutions, machine learning lifecycle management, data generation methods, model training, and evaluation. As well as possessing strong fundamentals and a passion for software engineering and system design. It is important to be able to dive into the latest academic/research advancement in ML, LLMs and NLP. As well as the ability to communicate complex technical ideas to diverse audiences, including research scientists, data scientists, engineers, designers, managers, and other partners across Siri and Apple.

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 the ability to balance multiple projects

Experience in the iOS development ecosystem (e.g. Swift, Objective-C, CoreML, or SiriKit)

Experience in localization, internationalization, machine translation, or language technologies is a great plus

Master's or PhD degree in computer science, software engineering, machine learning, language technologies, or related fields; outstanding candidates with Bachelor's degrees or equivalent experience and multiple years of significant engineering/product experience will also be considered

Minimum Qualifications

Proven experience developing, shipping, and measuring industry-scale machine learning-based software systems; experience working on large-scale LLM or NLU systems.

Expertise and experience in LLMs or other foundation models, ideally demonstrated through publications or shipping tools, foundation model-based features, and products.

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

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.