Staff ML Engineer: Generative Rec & RL at Scale

Pinterest Engineering; San Francisco (CA); On-site; USD 228,000 - 469,000; Full time

Job summary

Pinterest Labs is seeking a Staff Machine Learning Engineer, Applied Science to tackle ambitious challenges in generation and recommendation. You will lead the research, architecture, scale, and deployment of GenRec and RL solutions with a world-class team.

Collaborating with Product, Engineering, and Data Science, you will translate complex research into product impact, publish in top ML venues, and help shape the long-term research strategy while mentoring colleagues.

Qualifications

• 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.
• Publications at top ML conferences (e.g. KDD, NeurIPS, RecSys).
• Cross-functional collaborator and strong communicator.

Responsibilities

• Contribute to cutting-edge ML research across Ads, Discovery, Growth, and Search.
• Identify, scope, architect, build, and deliver novel ML solutions from 0 to 1 at scale.
• Identify new research opportunities by collaborating with external and internal partners.
• Partner with Product, Engineering, and Data Science to translate research into product impact.

Skills

Large-scale ML

Reinforcement learning

LLMs/VLMs

Cross-functional

Education

MS/PhD in CS

Job description

Pinterest Labs is seeking a Staff Machine Learning Engineer, Applied Science to tackle ambitious challenges in generation and recommendation. You will lead the research, architecture, scale, and deployment of GenRec and RL solutions with a world-class team.

Collaborating with Product, Engineering, and Data Science, you will translate complex research into product impact, publish in top ML venues, and help shape the long-term research strategy while mentoring colleagues.