Staff Machine Learning Engineer, Computer Vision

Pinterest; San Francisco (CA); Hybrid; USD 189,308 - 389,753; Full time

Job summary

Pinterest is seeking researchers and engineers to advance a cutting-edge visual encoder within the Labs’ Visual Modeling team. You will work with large visual-text datasets to train multimodal representations powering recommender systems and visual language features.

Responsibilities include prototyping state-of-the-art encoders, handling billion-scale datasets with GPU computing, and publishing results while mentoring interns. A strong ML background and publications are highly valued.

Qualifications

• Experience building and training computer vision models.
• Experience with multimodal representations and visual language modeling.
• Track record of research contributions or shipping ML models to production.
• Hands-on experience with large-scale model training and modern DL frameworks.

Responsibilities

• Prototype state-of-the-art visual encoders for recommender systems.
• Experiment with billion-scale datasets using GPU computing.
• Build flexible visual reasoning tools and generation models.
• Read papers, discuss research, and shape Pinterest's visual generative strategy.
• Mentor junior researchers and researchers interns within Labs.

Skills

Computer vision

Multimodal learning

Research experience

Collaboration

Education

MS/PhD in ML or related field

Tools

PyTorch

Cursor/Copilot/Codex

Job 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.

We are currently hiring for the Visual Modeling team in Labs, which develops Pinterest's in‑house visual encoder. 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. The visual encoder also produces visual tokens that power our in‑house VLM and composed image retrieval models. The core visual pod is a small group (~10 engineers) inside Labs, which allows for deep collaboration. For example, engineers working on multimodal representation also contribute to our internal text‑to‑image generation Canvas project—collaborating on autoencoder design or on reward function development for RL training.

What You’ll Do

• 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.

What We’re Looking For

• 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.
• Publications at top ML conferences.
• Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.

Relocation Statement

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

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.

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

US based applicants only

$189,308—$389,753 USD

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.