Jobs at Pinterest

Architect the infrastructure powering Pinterest’s Generative AI and recommender systems at petabyte scale. Set the AI Platform’s technical vision and roadmap, lead cross-functional initiatives spanning data orchestration, model training, fine-tuning, evaluation, feature stores, and high-performance inference, and drive company-wide architecture decisions. Foster an inclusive engineering culture while maintaining high standards for quality, ownership, and accountability.

Leads the technical direction and end-to-end delivery of machine learning and LLM systems for merchant quality, integrity, relevance, and shopping discovery. Responsibilities include architecture, implementation, evaluation, experimentation, monitoring, safety, scalability, and production rollout. The role establishes ML engineering standards, partners cross-functionally, mentors engineers, influences technical roadmaps, and supports future hiring while improving user trust and shopping outcomes.

Lead go-to-market strategy for Measure and Optimize products on Pinterest’s tvScientific team. Develop positioning, messaging, launch plans, enablement materials, and adoption programs for advertisers and agencies. Translate advertising technology, measurement, optimization, and data science concepts into compelling customer narratives. Partner cross-functionally with Product, Data Science, Sales, and Marketing teams to inform commercialization, monitor performance, and improve launches using customer, market, and competitive insights.

Build scalable data foundations, analytics tooling, analysis pipelines, and trusted self-service datasets for product and data science teams. The role focuses on instrumentation, experimentation standards, data quality, metric governance, documentation, workflow orchestration, and cross-functional collaboration. Engineers will use SQL, Python or R, and AI-assisted workflows while validating results and protecting sensitive data.

Leads product strategy and people management for Pinterest’s advertiser growth tools. Owns adoption, retention, revenue impact, and the Business Assistant platform strategy, including advertising and merchant sub-agents. Aligns Engineering, Data Science, TPM, Marketing, Sales, UX, and research teams to deliver scalable business tools. Requires experience with platform products, advertising or business-facing tools, AI-assisted chatbot or agentic capabilities, team development, and revenue-focused strategic execution.

Oversee Pinterest’s technology infrastructure finances, including AWS spending, forecasting, variance analysis, financial modeling, cost allocation, vendor management, and strategic investment decisions. Partner with Engineering, Infrastructure, and Technical Program Management teams to optimize infrastructure costs, predict resource needs, improve reporting processes, identify financial risks and opportunities, and apply AI tools to finance workflows.

Conducts end-to-end qualitative UX research for Pinterest’s monetization products, identifying knowledge gaps and delivering actionable insights. The researcher partners with Product, Design, Marketing, and senior leaders to influence product strategy and decisions. Responsibilities include selecting research methods, recruiting participants, researching AI-powered products, communicating findings compellingly, and shaping monetization initiatives across teams.

Lead go-to-market strategy for tvScientific’s CTV integration into Pinterest Ads Manager. Translate technical capabilities and performance insights into customer-focused positioning, messaging, launch programs, enablement materials, and adoption strategies. Partner cross-functionally with Product, Sales, Marketing, Data Science, and Pinterest Ads teams. Establish launch milestones, monitor adoption metrics, synthesize market and customer insights, and optimize commercialization efforts using data, feedback, and responsible AI-assisted research and content development.

Lead architecture and delivery of large-scale, low-latency distributed serving platforms supporting Pinterest Ads and Core experiences. Build highly available systems, modernize frameworks, improve APIs, experimentation, observability, and debugging, and drive initiatives from strategy through rollout and operational readiness. Partner across product, ML, infrastructure, Ads, and Core teams while mentoring engineers and establishing technical standards. The role requires strong expertise in production backend systems, technical leadership, scalability, reliability, and responsible AI-assisted engineering.

Lead Pinterest’s technical strategy and roadmap for scalable big data and AI infrastructure. Build frameworks for compute, job, resource, scheduling, and shuffle management across petabyte-scale datasets. Partner with internal customers, provide company-wide technical leadership, and improve data processing reliability, speed, and efficiency.

Designs user-focused content and information experiences for Pinterest’s personalized discovery surfaces, including Homefeed. Partners with product, design, engineering, research, and data science teams; uses research and data to improve clarity, trust, and engagement; develops scalable content frameworks and standards; and applies AI tools and prompting approaches throughout the content design process.

Lead the strategy, technical direction, and long-term roadmap for Pinterest’s big data and AI infrastructure. Build and scale frameworks for compute, job management, resource management, scheduling, and remote shuffling across petabyte-scale datasets. Partner with internal customers on critical big data use cases and provide company-wide technical leadership on reliable, efficient data processing and storage.

Design and implement scalable data infrastructure in AWS using Spark and Scala. Evolve core data pipelines, store data in optimal engines/formats, build knowledge graphs and APIs, optimize AWS resources, implement automated data quality checks, and collaborate with Data Science and Product teams to deliver reliable, large-scale data services.

Lead data-driven strategy for Pinterest Ads by translating business needs into analytical solutions, ensuring data quality, connecting product and financial performance, advising cross-functional leaders, and elevating data science practices across the organization.

Lead execution to productize Pinterest's Agent Platform from MVP to self-serve. Coordinate cross-functional stakeholders, define operating models, drive roadmap delivery, measure adoption and developer outcomes, and mentor teams to institutionalize scalable practices for AI/agent infrastructure.

Operate, scale, and harden an AWS- and Kubernetes-based platform using GitOps. Build CI/CD and infrastructure-as-code (Terraform/Terragrunt), manage ArgoCD/Helm deployments, improve observability, automate toil reduction, lead incident response and post-incident remediation, and partner with application, security, and platform teams to improve reliability and delivery.

Lead data science work for a CTV/adtech platform: write production Python code, design and analyze experiments, build reporting and analytics tools, translate insights into product, and collaborate with stakeholders to optimize ad campaigns.

Lead design and architecture of Oracle EBS revenue and finance systems, build integrations with SaaS and cloud platforms, drive ERP roadmap and SOX-compliant change processes, partner with Finance and Revenue stakeholders, and improve operational resilience and scalability.

Lead design and operation of identity resolution and data governance systems. Build batch and streaming pipelines, APIs, and tooling for identity ingestion, matching, lineage, quality, access controls, and privacy compliance (GDPR/CCPA). Collaborate with product, analytics, legal, and security to ensure privacy-by-design, monitoring, and documented runbooks.

Lead and grow a cross-functional engineering team building consumer-facing product areas. Set goals and drive roadmap execution, partner with Product/Design/Research/Data Science, coach engineers, support architecture and technical decisions, use data and experimentation to inform work, and apply AI responsibly to accelerate analysis and delivery while ensuring quality and verification.