Staff Machine Learning Engineer (Shopping Ads)

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 organization. This high-impact role offers the opportunity to make a direct impact on user trust, relevance, and shopping outcomes.

- Conduire des initiatives axées sur les LLM et l'évaluation, en mettant l'accent sur les flux de travail agentiques, la mesure et la rigueur opérationnelle. - Diriger la livraison technique de bout en bout pour des initiatives inter-équipes, de la définition du problème à la mise en œuvre et à l'itération. - 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 humaine.

- 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 - Strong systems design skills building data- and ML-intensive systems, with the ability to navigate tradeoffs in performance, reliability, scalability, and cost - Bachelor’s degree in Computer Science, Engineering, or a related technical field—or equivalent practical experience - Demonstrated ability to lead 0→1 ML/LLM efforts: taking ambiguous problem spaces, defining the approach, and delivering a production system with measurable impact - Strong communication skills and the ability to influence technical direction across teams without directly owning every implementation detail - Deep experience with evaluation and measurement: dataset strategy, labeling/review operations, metric design, regression testing, and connecting offline improvements to online outcomes - 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 - 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 experience building and enhancing cross-functional partnerships with other teams and organizations