Staff Machine Learning Engineer, Content Visual AI

At Pinterest, AI isn't just a feature, it's a powerful partner that augments creativity and amplifies impact. The User and Content Foundations org generates high-quality signals and insights that power relevance and personalization across the platform.

We are looking for an experienced Staff Machine Learning Engineer / Technical Lead who can drive the team's technical direction, lead the team in building scalable content understanding systems, and make an impact on core Pinterest user and business outcomes.

Responsibilities:

• Set the technical direction and multi-quarter strategy for foundational ML capabilities across visual representation learning, multimodal content understanding, and LLM-based personalization.
• Lead high-impact scientific and technical initiatives from problem definition and research strategy through experimentation, productionization, and adoption.
• Build reusable embeddings, representations, semantic signals, and ML infrastructure while advancing techniques such as VLMs, LLMs, sequence modeling, self-supervised learning, retrieval, and distillation.
• Partner with Product, Data Science, Applied Science, and Engineering to translate foundational capabilities into product outcomes and influence cross-functional roadmaps and investments.
• Establish rigorous practices for modeling, data pipelines, distributed training, inference, evaluation, experimentation, and operational excellence while mentoring engineers and scientists.

Requirements:

• Minimum 7 years of industry experience, including 2+ years of tech leading teams.
• MS or PhD degree in computer science, machine learning, or equivalent industry experience.
• Publications at top machine learning, multimodal and/or data mining conferences (e.g., NeurIPS, ICML, CVPR, ECCV, ACL, KDD, SIGIR, etc.) or open-source ML experience.
• Hands-on experience with large-scale distributed training of generative models (LLMs, VLMs, sequence models).
• Hands-on experience with distributed tooling for ML data pipelines (e.g. Spark, Hive, MapReduce).
• Hands-on experience leading ambiguous ML and research efforts in building, applying and improving GenAI models for content understanding, search and recommendation systems.
• Technical leadership and experience in setting direction for roadmaps that span modeling, data pipelines and productionization, and aligning stakeholders on priorities, trade-offs, and execution plans.
• Excellent cross-functional communication and collaboration skills.

Salary: $189,308-$389,753 USD