Machine Learning Engineer (Computer Vision Applied Science)
Posted Updated
Description
- Our visual modeling team is currently seeking new members to focus on the advancement of vision-centric LLMs. We are building VLMs capable of perceiving intricate visual details and understanding user aesthetics to facilitate communication through visual assets using tools like multimodal search and text-to-image models
- This role offers the opportunity to work with Pinterest’s unique visual-text datasets to develop large-scale generative models for production. You will join the core visual pod, a collaborative group of approximately six engineers and a product prototyping team, to create specialized evaluation benchmarks and contribute to the broader research community
- Prototype new model architectures for Pinterest VLMs. We’re looking for hands-on experience working with finetuning open-source LLM models and improve their visual perception and tool using capabilities
- Develop new evaluation benchmarks that tailors to vision-centric capabilities such as fashion style recommendations
- 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
- 2+ years of industry computer vision experience
- Research engineers and scientists who have experience working with generative computer vision models, preferably various forms of visual encoders and LLMs
- M.S. or PhD in Machine Learning, Computer Science, or related areas
- Publications at top ML conferences
- 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