Staff Machine Learning Engineer – Apple – Toronto, Ontario

Apple’s News, Books, and Stocks team in Toronto, Ontario is looking for a Staff Machine Learning Engineer to help shape the next generation of apps used by millions of people every day. This distributed team brings together talented client and ML engineers who take pride in their craft, support one another, and consistently push the boundaries of what’s possible in machine learning.

The work here spans some genuinely challenging ML problems — from text extraction and named entity recognition to search, ranking, and duplicate detection — all applied to the fast-evolving worlds of news, books, and financial data. If you’re motivated by hard problems and meaningful impact, this role puts you right at the centre of it.

About the Role: Staff Machine Learning Engineer

As a Staff Machine Learning Engineer, you’ll play a central role in delivering scalable ML services that power Apple News, Apple Books, and Stocks. You’ll work on a distributed, cross-functional team, collaborating with interdisciplinary partners to design and ship user-facing machine learning features at scale. The role carries real ownership — from model development through to production deployment.

The team values open collaboration, intellectual curiosity, and a genuine commitment to quality. You’ll have the opportunity to contribute to both the technical direction and the culture of a group known for its strong retention and mutual respect. Inclusive practices and thoughtful communication are core expectations here, not afterthoughts.

Benefits and Salary

Apple is known for offering a comprehensive total compensation package, which typically includes health and dental benefits, employee stock purchase plans, paid time off, and access to Apple’s internal learning and development resources. Specific compensation details were not listed in this posting, but Apple’s investment in its people is well-established.

Responsibilities

Day to day, you’ll be tackling complex machine learning challenges across the news, books, and stocks domains — building and deploying models that directly affect how millions of users experience Apple’s content apps. These responsibilities require both technical depth and strong cross-functional communication.

• Design and ship user-facing machine learning features in collaboration with interdisciplinary partners
• Build and deploy scalable ML services that operate reliably in production environments
• Develop models for tasks such as text extraction, named entity recognition, duplicate detection, search, and ranking
• Apply expertise in recommender systems to surface relevant content for Apple’s users
• Work with text-centric AI/ML approaches including LLMs, document classification, and search
• Collaborate closely with partner teams to deliver high-quality software at scale
• Contribute to an open and inclusive team culture through thoughtful communication and mentorship

Requirements / Skills

This role is best suited to engineers who have hands-on experience shipping ML models in production and who are comfortable owning complex technical problems end to end. Apple values both technical rigour and the ability to work effectively across teams and disciplines.

• Master’s degree in Machine Learning, Computer Science, or a related field — or equivalent industry experience
• 5+ years of experience shipping machine learning models in real-world products
• Strong programming skills in Python, Java, or a related language, combined with experience in deep learning frameworks such as PyTorch or TensorFlow
• Recommender systems experience with a solid understanding of how to build and evaluate them
• Text-centric AI/ML expertise, including work with LLMs, document classification, or search systems
• Ph.D. in Machine Learning or Computer Science is considered an asset, as is prior experience in a technical leadership role

How to Apply

To apply for this Staff Machine Learning Engineer position at Apple in Toronto, visit the official job posting using the link below. Make sure your resume is up to date and reflects your most relevant ML experience before submitting.

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