Sr. Machine Learning Engineer, Applied Science

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 .

Within Pinterest, the Pinterest Labs organization focuses on applied ML research and development. Labs focuses on a broad variety of AI/ML initiatives, such as core computer vision, multimodal representation learning, heterogeneous graph neural networks, generative modeling, recommender systems, etc. This is the group that develops foundation ML models that fully leverage the tens of billions of Pins and the associated knowledge graph to improve the core product.

We are currently hiring for the visual modeling team in Labs, which focuses on developing Pinterest Canvas. Canvas is a foundation text-to-image model developed internally for helping various visualization, inpainting, and outpainting products. In this role, you’ll get to work with Pinterest’s rich visual-text dataset to build large-scale generative models which are continuously being shipped to production to power visualization features. The core Canvas pod is a small group (~6 engineers along with a product prototyping team) inside of Labs, allowing for deep collaboration. For example, engineers working on the Canvas project also participate in the development of our core multimodal text & image embeddings, as these are in turn used to condition the model in unique ways.

What you’ll do:

• Prototype new model architectures for Pinterest Canvas, our internal text-to-image generative model. We’re looking for hands-on experience working with diffusion text-to-image models and independent model implementation skills.


• Read research papers, participate in group discussions, and help brainstorm our overall visual generative strategy at the company.


• Help with collection of relevant visual training data for Pinterest Canvas, particularly to conduct RLHF, targeted fine-tuning, etc.


• Publish and publicize your work via conferences, paper submissions, blog posts, etc. 


• Mentor more junior researchers or research interns within the Pinterest Labs organization.

What we’re looking for:

• Research engineers and scientists who have experience working with generative computer vision models, preferably various forms of diffusion models.


• 5+ years of industry computer vision experience.


• M.S. or PhD in Machine Learning, Computer Science, or related areas.

Nice to Have:

• Publications at top ML conferences.


• Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.


• Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.


• This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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