Sr. Staff Machine Learning Engineer, Content Ecosystem

Pinterest; San Francisco (CA); On-site; USD 227,871 - 469,147; Full time

Job summary

Pinterest is seeking a Machine Learning Engineer to oversee technical strategy and optimization for its content ecosystem. This role involves collaboration across various teams to develop frameworks that assess content performance and improve long-term ecosystem values.

Candidates should have expertise in machine learning, strong leadership capabilities, and experience with AI development tools. The position requires US-based applicants and offers a competitive salary range.

Qualifications

• Strong fundamentals in machine learning and optimization.
• Ability to manage multi-objective tradeoffs effectively.
• Experience developing solutions for high-scale ecosystem problems.

Responsibilities

• Set technical strategy for ML systems to improve content ecosystem.
• Develop measurement frameworks for content health and performance.
• Mentor junior ML engineers and enhance engineering quality.

Skills

Machine learning fundamentals

Optimization skills

Technical strategy leadership

Experience with AI coding assistants

Familiarity with LLM tools

Background in game theory

Education

Degree in Computer Science or Engineering

Job description

What you will 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 beneficial—for example, game‑theoretic approaches, reinforcement learning, mechanism design, or bandit‑style optimization—to improve marketplace dynamics and long‑term ecosystem outcomes.

What we're 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.

US based applicants only

Salary range: $227,871 — $469,147 USD

Our Commitment to Inclusion

Pinterest is an equal‑opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition or genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.