Staff Machine Learning Engineer

Pinterest • San Francisco, CA

20h • Remote

About The Position

Growth Content Science builds the machine learning systems that decide which content appears on Pinterest’s growth surfaces, with a focus on notifications. The team owns the real-time production stack for these decisions, including candidate retrieval, L1 and L2 ranking, utility and blending, content quality, and copy generation and ranking. The Staff Machine Learning Engineer will build complex models and systems, uphold code quality and healthy ML infrastructure, and lead the technical direction for notification content ranking.

The role leads technical work across Growth Content Science, drives model improvements through an A/B-test-driven process from ideation to production launch, and owns the health of the ML ecosystem. It also contributes to technical direction and roadmaps, raises engineering standards through mentorship and review, collaborates across functions, and applies relevant research and AI tools to improve the work.

Requirements

• Graduate degree in Computer Science or a related field.
• At least 8 years of experience in machine learning engineering, including hands-on experience building and shipping models for a large-scale, real-time, end-user production recommender system.
• Expertise in recommender modeling, including sequence modeling of user behavior with transformer architectures, DNN rankers, and generative and LLM-native recommenders.
• Experience building and operating high-QPS, latency-constrained ML systems, including training and serving infrastructure, and managing cost, latency, and reliability tradeoffs.
• Experience in industry-grade software engineering and conducting thorough code and design reviews that raise a team’s work quality.
• Understanding of content personalization and content quality as interconnected problems, including why cold-start and low-signal users challenge standard rankers.
• Experience leading technical work across teams, making timely decisions on difficult tradeoffs, and prioritizing user experience and system health.
• Experience mentoring junior engineers.
• Outstanding written and verbal communication skills, especially in cross-functional settings.
• Demonstrated experience using AI to improve the speed and quality of applied research.
• Strong track record of publications and patents.

Responsibilities

• Lead multiple technical sub-areas within Growth Content Science.
• Drive Growth ML model improvements through an A/B-test-driven innovation loop, from ideation to production launches.
• Own the health of the ML ecosystem, including training pipelines, feature and serving infrastructure, evaluation frameworks and monitoring, and A/B test setup.
• Raise technical excellence through mentorship, reviews, evaluations, documentation, and setting standards.
• Collaborate with colleagues and stakeholders on large cross-functional initiatives.
• Work with engineering leaders to establish technical directions and roadmaps.
• Operate autonomously, take ownership in complex and evolving environments, and drive work effectively.
• Identify and apply relevant state-of-the-art techniques from recent research and/or collaborate on novel research directions.
• Continuously optimize work by building and using cutting-edge AI tools.
• Build complex models and systems for the growth content ML stack and lead technical direction for notification content ranking.

What This Job Offers

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