Sr. Staff Machine Learning Engineer, Content Ecosystem

About Pinterest:

Millions of people around the world come to our platform to find creative ideas dream about new possibilities and plan for memories that will last a lifetime. At Pinterest were on a mission to bring everyone the inspiration to create a life they love and that starts with the people behind the product.

Discover a career where you ignite innovation for millions transform passion into growth opportunities celebrate each others unique experiences and embrace theflexibility to do your best work. Creating a career you love Its Possible.

At Pinterest AI isnt just a feature its a powerful partner that augments our creativity and amplifies our impact and were looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities well explore your foundational skills and how you collaborate with AI.

Through our interview process what matters most is that you can always explain your approach showing us not just what you know but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

Pinterest works when the content ecosystem works: when people can reliably find ideas that feel inspiring trustworthy and actionableand when the ecosystem continuously learns what to create surface and sustain this Sr. Staff ML Engineer role youll be the technical lead shaping how Pinterest understands and improves its content as a living marketplace: a dynamic system with feedback loops between users creators/publishers distribution and long-term business outcomes.

You will define a durable ML strategy that goes beyond engagement metrics to improve overall ecosystem healthidentifying where were underserving content uncovering the attributes that make content succeed and designing optimization approaches that balance relevance quality diversity integrity and monetization. The problems are inherently multi-objective and long-horizon: the best decisions today should strengthen the ecosystem tomorrow. If youre excited by high-leverage technical leadership rigorous ML thinking and marketplace-style dynamics at scale this role offers a chance to directly shape Pinterests moat and the experience millions of people come to for ideas they can act on.

What youll do:

• Set technical strategy and vision for ML systems that improve the end-to-end content ecosystem including supply distribution and engagement/utility outcomes.
• Partner with DS teams to develop a content ecosystem measurement framework to quantify content health and performance (e.g. content quality freshness diversity coverage creator/content sustainability and user value) and align it with company/business goals.
• Identify and close content gaps by building models and insights that answer: what content is missing for whom in which contexts and why.
• Deeply understand what content works and why by combining causal thinking experimentation and model interpretability to connect content attributes and distribution mechanisms to downstream user and business outcomes.
• Build and optimize content marketplace mechanisms that balance multi-sided incentives and constraints (e.g. users creators/publishers advertisers internal policy/safety) while maximizing long-term ecosystem value.
• Design multi-objective optimization approaches that manage tradeoffs across relevance quality diversity creator incentives integrity/safety and monetization.
• Partner closely with cross-functional teams (Product Data Science UX Research Content/Creator teams Trust & Safety Ads Infra) to translate ambiguous ecosystem problems into clear technical roadmaps and deliver measurable impact.
• Mentor and grow junior ML engineers through technical coaching design reviews career development support and creating a culture of strong engineering and scientific rigor.
• Raise the quality bar for ML engineering by establishing best practices for data quality model governance reliability privacy-aware design and operational excellence.
• Communicate clearly and influence broadly by producing crisp technical proposals aligning stakeholders on tradeoffs and driving decisions across org boundaries.
• Explore and apply advanced methods where beneficiale.g. game-theoretic approaches reinforcement learning mechanism design or bandit-style optimizationto improve marketplace dynamics and long-term ecosystem outcomes.

What were looking for:

• Strong fundamentals in machine learning and optimization with the ability to apply them to real-world high-scale ecosystem problems.
• Demonstrated ability to lead technical strategy navigate ambiguity and deliver end-to-end impact.
• Deep interest in marketplace dynamics (multi-sided incentives feedback loops long-term health metrics) and comfort with multi-objective tradeoffs.
• Experience with 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.
• Not required but certainly a plus: background in game theory reinforcement learning mechanism design or causal inference applied to ecosystems/marketplaces.
• Degree in Computer Science Engineering a related field or equivalent experience.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

• We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
• This role will need to be in the office for in-person collaboration 1-2 times every 6 months and therefore can be situated anywhere in the country.

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