Staff Machine Learning Engineer (Shopping Merchants)

Join Pinterest as a Staff Machine Learning Engineer, where you'll drive the future of merchant presence and shopping experiences. You'll lead AI/ML initiatives, partner with cross-functional teams, and establish the technical roadmap for the Merchant team. This high-impact role offers the opportunity to shape user trust, relevance, and shopping outcomes on Pinterest.

• Conduire des initiatives axées sur les LLM et l'évaluation, en mettant l'accent sur les flux de travail agentiques, la mesure et le respect opérationnel.
• Construire et faire évoluer des systèmes d'IA et de ML qui améliorent la qualité et la compréhension des marchands, avec un impact clair sur la récupération, le classement et les surfaces de shopping.
• Établir des pratiques d'évaluation et de mesure robustes pour les systèmes assistés par ML et LLM, y compris les ensembles de données d'or, les boucles de révision humaines, les tests de régression automatisés.
• 8+ years of industry experience in ML engineering / applied ML / software engineering, including meaningful time operating as a Staff-level (or equivalent) IC delivering complex production systems
• Demonstrated ability to lead 0→1 ML/LLM efforts: taking ambiguous problem spaces, defining the approach, and delivering a production system with measurable impact
• Demonstrated experience building and enhancing cross-functional partnerships with other teams and organizations
• Strong track record shipping ML-powered systems in domains such as recommendation, ranking, retrieval, content understanding, ads relevance, commerce, or adjacent areas with clear product impact
• Strong communication skills and the ability to influence technical direction across teams without directly owning every implementation detail
• Strong systems design skills building data- and ML-intensive systems, with the ability to navigate tradeoffs in performance, reliability, scalability, and cost
• Deep experience with evaluation and measurement: dataset strategy, labeling/review operations, metric design, regression testing, and connecting offline improvements to online outcomes
• Hands-on experience building LLM-powered applications in production (or adjacent GenAI systems), with strong judgment on reliability, failure modes, rollout safety, and practical tradeoffs
• Bachelor’s degree in Computer Science, Engineering, or a related technical field—or equivalent practical experience