Staff Machine Learning Engineer (Content Visual AI)

Join Pinterest as a Staff Machine Learning Engineer in the User and Content Foundations organization. In this role, you will drive the team's technical direction, lead the development of scalable content understanding systems, and make a significant impact on core user and business outcomes. You will work across research, machine learning, infrastructure, and engineering domains to turn advances in visual language models, large language models, multimodal learning, and sequence modeling into tangible results.

- Lead the team in building scalable content understanding systems and drive the technical direction of the team. - Set the technical direction and multi-quarter strategy for foundational ML capabilities across visual representation learning, multimodal content understanding, and LLM-based personalization. - Establish rigorous practices for modeling, data pipelines, distributed training, inference, evaluation, experimentation, and operational excellence while mentoring engineers and scientists.

- Expertise in visual representation learning and content understanding is especially valuable; experience with user understanding, recommender systems and LLMs is also highly relevant - This role is ideal for a deeply technical leader who combines strong ML judgment with product intuition - Hands-on experience with large-scale distributed training of generative models (LLMs, VLMs, sequence models) - 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 leading ambiguous ML and research efforts in building, applying and improving GenAI models for content understanding, search and recommendation systems - Minimum 7 years of industry experience, including 2+ years of tech leading teams - 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 - Hands-on experience with distributed tooling for ML data pipelines (e.g. Spark, Hive, MapReduce)