Staff Machine Learning Engineer, Homefeed

Pinterest • San Francisco, CA

5d • Remote

About The Position

Pinterest’s Retrieval team builds shared machine learning capabilities that connect people with relevant ideas. The Staff Machine Learning Engineer will advance these capabilities through agentic AI, with a primary focus on Reflex, an effort to automate and accelerate recommendation research and development. The engineer will own a major technical area and build agents that investigate opportunities, implement changes, run experiments, and learn from results, while working closely with technical leaders and remaining hands-on with challenging engineering and modeling problems.

The role also contributes to generative retrieval, particularly Semantic IDs: structured content representations that recommendation models can generate and use to retrieve relevant items. It combines applied AI research, production engineering, and technical leadership to improve both recommendation models and the way engineers build them. The role is an individual contributor position; prior people management is not required. The position can be based anywhere in the country and requires in-office collaboration 1–2 times per quarter.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
• At least 8 years of experience building and shipping ML or AI systems, including substantial hands-on engineering and technical leadership.
• Demonstrated experience building LLM agents or other agentic AI systems for complex tasks, with a clear approach to evaluating and improving their performance.
• Strong ML fundamentals and depth in one or more relevant areas, such as applied LLMs, representation learning, recommendation systems, retrieval, or ML systems.
• Experience taking research ideas into reliable production systems and evaluating their impact through meaningful experiments.
• Strong software engineering skills, including designing maintainable systems, implementing difficult components, and conducting thorough technical reviews.
• Experience leading a substantial technical area, making decisions under ambiguity, and collaborating effectively across teams.
• Track record of mentoring engineers and raising the quality of a team’s technical work.
• Clear written and verbal communication, including the ability to explain technical tradeoffs to different audiences.
• Disciplined use of AI in one’s own work, including verification of generated code, analysis, and conclusions.

Responsibilities

• Own and advance a major technical area in automated recommendation research within Reflex, collaborating with technical leads and partner teams.
• Build LLM agents that connect hypothesis generation, implementation, experiment execution, evaluation, and learning from previous results.
• Develop rigorous evaluations for agent behavior and research outputs, and use them to improve quality, reliability, and efficiency.
• Contribute to generative retrieval models, particularly Semantic ID learning, evaluation, and integration into production recommendation systems.
• Move promising ideas from research and prototypes through offline evaluation, online experimentation, and production launches.
• Build reliable integrations with ML development infrastructure and make tradeoffs across model quality, iteration speed, compute cost, and operational complexity.
• Raise technical quality through hands-on implementation, design and code reviews, documentation, and mentorship.
• Work with research, recommendation, and ML infrastructure teams to shape technical approaches, resolve dependencies, and support adoption.
• Identify and apply relevant research advances, and contribute new methods where existing approaches fall short.

What This Job Offers

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