Staff Machine Learning Engineer

Pinterest • San Francisco, CA

12h • Remote

About The Position

As part of Pinterest Labs, the Staff Machine Learning Engineer will work with research scientists and machine learning engineers on machine learning and artificial intelligence challenges. The role focuses on transforming content discovery on Pinterest through research, architecture, scaling, and production deployment of Generative Recommendation System (GenRec) and reinforcement learning solutions. The position also conducts research applicable across Pinterest engineering teams, supports external collaborations and mentoring, and works at the intersection of recommendation systems, LLMs, VLMs, and reinforcement learning.

The role is remote-capable anywhere in the country, with in-office collaboration required 1–2 times per quarter. Relocation assistance is not available.

Requirements

• MS/PhD in Computer Science, or equivalent industry experience.
• Minimum 6 years of relevant industry experience.
• Hands-on experience with large-scale recommendation systems and reinforcement learning applications.
• Technical leadership and experience driving ambiguous research problems into production deliverables.
• Publications at top machine learning conferences such as KDD, NeurIPS, or RecSys.
• Ability to collaborate cross-functionally and communicate effectively.

Nice To Haves

• Experience with LLM/VLM post-training.

Responsibilities

• Contribute to cutting-edge AI/ML research applicable to Pinterest challenges across Ads, Discovery, Growth, and Search.
• Identify, scope, architect, build, and deliver novel, end-to-end machine learning solutions from 0 to 1 at scale.
• Identify timelines and obtain the resources needed for work.
• Identify emerging research opportunities through engagement with internal and external collaborators.
• Own long-term research strategy and plans to expand the impact of Applied Science.
• Act as a technical leader in applied AI.
• Partner with Product, Engineering, and Data Science to translate complex engineering solutions into product impact.
• Conduct research in recommendation systems, LLMs, VLMs, and reinforcement learning.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior