Senior Machine Learning Engineer (Applied Science)
Posted Updated
Description
- 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
- 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
- Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
- Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
- 5+ years of industry computer vision experience
- M.S. or PhD in Machine Learning, Computer Science, or related areas
- Research engineers and scientists who have experience working with generative computer vision models, preferably various forms of diffusion models
- Publications at top ML conferences