Synced from Greenhouse · Oct 14

University Grad Machine Learning Engineer 2027 (Zurich)

PinterestZurich, CHPosted Oct 14, 2026
Machine Learning EngineerJunior
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Mirrored from Pinterest's own Greenhouse careers system · refreshed hourly

$134k–$154k
Compensation
162
Other open Pinterest roles
Oct 14
Posted
Greenhouse
Applicant system
Job descriptionReq 8267930

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 product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

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.


What you’ll do:

  • 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.
  • Experience applying machine learning or AI concepts through research, coursework, projects or internships.
  • Use AI to accelerate analysis and iteration while applying judgment and verification to ensure correctness and quality.

What we’re looking for:

  • 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 realtime systems that process stream data
  • Mastery of at least one systems languages (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

In-Office Requirement:

  • This role will need to be in the office for in-person collaboration 2-3 weekdays per week and therefore needs to be within a commutable distance of Zurich.

Relocation Statement:

  • This position may be eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
  • Information regarding the culture at Pinterest and benefits available for this position can be found here.

The minimum and maximum salary for this position is $133,600-153,600.

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Our Commitment to Inclusion:

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.
 
By submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. I understand that any false statement, omission, or misrepresentation may disqualify me from employment consideration or result in termination if discovered after hire.
View original posting on Greenhouse

What applying to Pinterest usually looks like

Based on publicly available information, candidates applying through greenhouse for Pinterest can typically expect a structured application process common to this ATS platform. After submitting an application, candidates may receive an initial acknowledgment, though response times vary and are not guaranteed. The process commonly includes an initial recruiter screen, followed by additional conversations with hiring managers or team members, and may include multiple stages such as technical assessments, portfolio reviews, or case studies depending on the role type. Communication is generally handled through the Greenhouse platform, which may send automated status updates. Candidates are encouraged to review the job description closely, tailor application materials accordingly, and prepare for a process that could involve several steps before a final decision is reached. Following up politely, if needed, is generally considered acceptable practice.

Based on publicly available information. LandEarly does not verify interview process details.

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University Grad Machine Learning Engineer 2027 (Zurich)
Pinterest · Zurich, CH
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