Description
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.
Within Pinterest, the Pinterest Labs organization focuses on applied ML research and development. Labs works across a broad variety of AI/ML initiatives,including core computer vision, multimodal representation learning, heterogeneous graph neural networks, generative modeling, and recommender systems.
In this role, you'll work with Pinterest's rich visual-text dataset to train large-scale models from scratch that are continuously shipped to production to power visualization features. You'll build multimodal representations that power applications such as recommender systems, Semantic IDs, and a range of downstream ML models.
Responsibilities:
- Prototype state-of-the-art visual encoders that power Pinterest's recommender systems and internal visual language models.
- Experiment with billion-scale datasets and gain hands-on experience with large-scale GPU computing.
- Build flexible visual reasoning tools such as composed image retrieval, promptable detection/segmentation, and instruction-tuned embedding and generative models.
- Read research papers, participate in group discussions, and help brainstorm the company's overall visual generative strategy.
- Help collect relevant visual instruction training data that can be shared across multimodal representation, composed image retrieval, text-to-image generation and visual language modeling.
- Publish and share your work through conferences, paper submissions, and blog posts.
- Mentor junior researchers and research interns within the Pinterest Labs organization.
Requirements:
- Research engineers and scientists with experience building and training computer vision models.
- Experience with multimodal representations and visual language modeling is strongly preferred.
- A track record of research contributions (e.g., publications, open-source work) and/or shipping ML models to production.
- Hands-on experience with large-scale model training and modern deep learning frameworks (e.g., PyTorch).
- Strong collaboration skills and a demonstrated ability to work effectively in a small, fast-moving team.
- M.S. or PhD in Machine Learning or related academic areas, or equivalent work experience.
Benefits:
- The position is eligible for equity.
- Base salary range: $189,308-$389,753 USD