Sr. Staff Machine Learning Engineer, Content Quality
About the position At Pinterest, AI is a powerful partner that augments creativity and amplifies impact. We are looking for candidates excited to be part of this. This role is for a Sr. Staff Machine Learning Engineer to be the Technical Lead for Content Quality. The individual will build the overall technical strategy, unified technical architecture, and define a roadmap for industry-leading methodology. The role requires a strong hands-on machine learning background, including content modeling, signal lifecycle, and platforms used to enforce signal use with downstream use cases. The engineer will work with other leads to set and execute a long-term strategy for the team, aligning it with other clients where appropriate, and communicating current status and the path to world-class capabilities to leadership. Additionally, the role involves fostering a healthy community where Content Quality engineers can learn best practices, collaborate effectively, and understand the technical direction.
Responsibilities
- Architect and develop a roadmap and processes for building and delivering signals capturing quality and trust aspects of content at Pinterest.
- Drive safety of GenAI and Conversational use cases including safety alignment and VLMs.
- Work with downstream teams to align on use cases, evaluate signal impact, and drive adoption of signals in models, ranking systems, and decision-making workflows.
- Partner closely with ML engineers to translate ideas into production-ready signals, from problem formulation and feature design to validation and deployment.
Requirements
- Experience driving technical strategy at an organizational level.
- Expertise in content modeling at consumer internet scale.
- Using GenAI for scaling ML development.
- Strong ability to work cross-functionally and with partner engineering teams.
- Experience working with multiple stakeholders.
- Strong measurement and scalability experience.
- Strong ML knowledge and expertise.
- Machine Learning at scale deployment experience
Nice-to-haves
- Hands-on experience with big data technologies (e.g., Hadoop / Spark / Kafka / Flink) is a plus.
- Thought Leadership: Publication and/or conference speaking experience is a plus.
- Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
- Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.
Benefits
- Equity
- Base salary range: $268,084—$469,147 USD
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