Pinterest is hiring a remote Staff Machine Learning Engineer!
Pinterest is hiring a Staff Machine Learning Engineer and technical lead for its User and Content Foundations organization, a team that builds reusable signals and insights about content and users to power personalization and relevance across Discovery, Search, Growth, and Ads. The position is remote within the United States, with in-person collaboration expected roughly one to two times per quarter, and no relocation support is offered. This is a senior individual-contributor leadership role for someone who blends deep machine learning judgment with product intuition and can steer multi-quarter strategy at the intersection of large multimodal models, distributed training, data infrastructure, and product adoption. The base salary range is $189,308 to $389,753 USD, with equity also part of the package.
Key responsibilities
- Define the technical direction and multi-quarter roadmap for foundational ML work spanning visual representation learning, multimodal content understanding, and LLM-driven personalization
- Lead scientific and engineering initiatives end to end, from problem framing and research strategy through experimentation, productionization, and partner adoption
- Build reusable embeddings, semantic signals, and ML infrastructure while advancing techniques such as vision-language models, LLMs, sequence modeling, self-supervised learning, retrieval, and distillation
- Collaborate with Product, Data Science, Applied Science, and Engineering partners to convert foundational capabilities into measurable product outcomes and to shape cross-functional roadmaps
- Set rigorous standards for modeling, data pipelines, distributed training, inference, evaluation, and experimentation, and mentor engineers and scientists across the team
Key requirements
- At least 7 years of industry experience, including 2 or more years leading teams technically
- MS or PhD in computer science, machine learning, or comparable industry experience
- A track record of publications at venues such as NeurIPS, ICML, CVPR, ECCV, ACL, KDD, or SIGIR, or meaningful open-source ML contributions
- Hands-on experience with large-scale distributed training of generative models, including LLMs, VLMs, and sequence models
- Practical familiarity with distributed data tooling for ML pipelines such as Spark, Hive, or MapReduce
- Demonstrated ability to lead ambiguous ML and research efforts that build and improve GenAI models for content understanding, search, and recommendation
- Experience setting technical roadmaps across modeling, data pipelines, and productionization, and aligning stakeholders on priorities and trade-offs
- Strong cross-functional communication and collaboration skills
- Seniority: Staff
- Work mode: Remote (US-based; in-office collaboration 1-2 times per quarter)
- Salary: $189,308 - $389,753 USD
- Key skills: Machine learning, Visual representation learning, Multimodal content understanding, LLMs, VLMs, Sequence modeling, Self-supervised learning, Retrieval, Distillation, Distributed training, Spark, Hive, MapReduce, Recommender systems, Technical leadership
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