Machine Learning Engineer II, Core Engineering
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the produ
What this role actually needs.
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the produ Responsibilities: - Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest - Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas - Use data driven methods and leverage the unique properties of our data to improve candidates retrieval - Work in a high-impact environment with quick experimentation and product launches - Keeping up with industry trends in recommendation systems - 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning) Requirements: - 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning) - End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark) - M.S. or PhD in Machine Learning or related areas - Expertise in scalable realtime systems that process stream data - Passion for applied ML and the Pinterest product - Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring. Company context: Pinterest is the visual discovery platform that powers idea search and shopping across web and mobile.
Day-to-day expectations
Pinterest lists these responsibilities for the Machine Learning Engineer II, Core Engineering role.
- Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
- Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
- Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
- Work in a high-impact environment with quick experimentation and product launches
- Keeping up with industry trends in recommendation systems
- 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
What a strong candidate brings
These requirements are extracted from the source listing and normalized for UpJobz readers.
- 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
- End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
- M.S. or PhD in Machine Learning or related areas
- Expertise in scalable realtime systems that process stream data
- Passion for applied ML and the Pinterest product
- Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
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Machine Learning Engineer II, Core Engineering is framed against UpJobz source checks, country scope, compensation visibility, and work-authorization signals so candidates can make a faster go/no-go decision.
Canada tech market
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Current extracted signal: Open to TN, H-1B, and OPT candidates already in the United States. UpJobz treats this as a search signal, not legal advice, and links visa-sensitive roles back to the relevant visa hub where possible.
Location read
On-site roles in Toronto should be compared against commute, local salary bands, and nearby employer demand.
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Next moves
- Tailor your resume around ai and llm instead of sending a generic application.
- Use the first two bullets of your application to connect your background directly to machine learning engineer ii, core engineering is a high-signal on-site role in toronto, and it is most realistic for open to tn, h-1b, and opt candidates already in the united states.
- Open the role quickly if it fits and bookmark three similar jobs before you leave the page.
Interview themes
Watchouts
- Compensation is hidden, so get range clarity in the first recruiter conversation.
- Use open to tn, h-1b, and opt candidates already in the united states as part of your positioning so the recruiter does not have to infer it.
- Show concrete examples of succeeding in on-site environments.
Keywords to match against your background
Use these terms to decide whether your resume, portfolio, and recent projects line up with the role.
Apply through the employer source
Open the source listing from pinterestcareers.com, confirm the role is still active, then apply on the employer or ATS page.
Source: pinterestcareers.com · Source ID: 7473497 · Confidence: 90/100 · Last checked: May 7, 2026
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