University Grad Machine Learning Engineer 2027 (Zurich)

As a Machine Learning Engineer at Pinterest, you'll develop and improve machine learning systems that power product experiences and discovery.

You'll partner with engineering, product, and design teams to build, evaluate, and iterate on scalable solutions that help Pinners find relevant, inspiring content.

In this role, you'll grow your technical expertise while contributing to reliable, high-impact systems.

Responsibilities:

• Conduct applied machine learning research to address product and platform challenges at Pinterest.
• Collect, analyze, and synthesize data to develop data-driven machine learning models.
• Write maintainable, efficient code and contribute to testing and code-review practices.
• Apply machine learning techniques, including natural language processing and graph-based approaches, to modeling and ranking challenges across discovery, ads, and search.
• Design, build, and test recommendation and engagement-prediction models that improve push, email, and in-app notification experiences.
• Develop and iterate on large-scale applied machine learning systems, using evaluation results to improve model performance and reliability.
• Scope, implement, and deliver solutions for moderately complex ML problems, escalating risks and tradeoffs as needed.

Requirements:

• Master's in Computer Science, ML, NLP, Statistics, Information Sciences, or related field required.
• Machine Learning experience (ranking, computer vision, NLP, content recommendations, embedding, information retrieval, etc.).
• Experience with big data technologies (e.g., Hadoop/Spark) and scalable real-time systems that process stream data.
• Mastery of at least one systems language (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow).
• Cross-functional collaborator and strong communicator.
• Comfortable solving ambiguous problems and adapting to a dynamic environment.
• Experience in research and in solving analytical problems.

Benefits:

• The minimum and maximum salary for this position is $133,600-153,600.
• Relocation assistance may be eligible.
• In-office requirement: 2-3 weekdays per week in the Zurich office.