Pinterest

This internship focuses on developing and launching new user features using ML techniques, particularly in computer vision, generative AI, and responsible AI, within Pinterest's Advance Technology Group (ATG). The role involves hands-on experience with production ML systems, from research to inference and product deployment, leveraging frontier AI tools and agents. Interns will validate AI outputs, contribute to research, write production code, and take ownership of tasks, with a specific focus on Visual Search, Generative AI, and LLMs.

Principal Engineer role focused on building the foundational platform and capabilities for AI agents to operate within Pinterest's software development lifecycle. This includes architecting agent runtimes, memory systems, orchestration frameworks, evaluation pipelines, and governance models to enable 3,000+ engineers to build alongside AI agents safely and at scale. The role involves shipping production systems, owning developer velocity measurement, and serving as a technical advisor to leadership.

This role focuses on designing and building data science foundations for automated adversarial testing of Generative AI products at Pinterest. The primary goal is to identify vulnerabilities, develop evaluation frameworks, and create harm-detection methodologies to ensure product safety, policy compliance, and user trust. The role involves working cross-functionally with ML Engineers, Trust & Safety, Policy, and Product Managers to proactively mitigate risks in GenAI experiences.

Senior Data Scientist role focused on building the measurement and evaluation frameworks for foundational AI models at Pinterest. This role will design system-level metrics, experimentation strategies, and causal inference methodologies to quantify the impact of model improvements on user and business outcomes, directly influencing investment decisions and launch criteria. The role requires deep understanding of recommendation systems and large-scale ML evaluation.

Sr. Staff Machine Learning Engineer, Content Quality at Pinterest. This role involves architecting and developing signals for content quality and trust, driving safety for GenAI and conversational use cases, and partnering with ML engineers to deploy production-ready signals. The role also requires aligning with downstream teams on use cases and signal adoption, and working cross-functionally to set and execute long-term strategy. Experience with big data technologies and ML at scale deployment is a plus.

PhD Machine Learning Intern role focused on developing and launching new user features using ML techniques in recommendation systems, computer vision, generative AI, and responsible AI. The role involves research, production ML systems, and leveraging frontier AI tools, with potential for paper submissions or deploying features to millions of users.

VP, Ads Quality Engineering to spearhead the AIML engineering division, leveraging data, machine learning, and generative AI to enhance Pinterest's ads delivery funnel. This role requires strong analytical skills, deep understanding of ML and generative AI, online auction dynamics, and experience leading large engineering teams to maximize monetization opportunities.

Sr. Machine Learning Engineer focused on Responsible AI, working on bias identification and mitigation, Gen AI alignment, safety fine-tuning, and Red Teaming. Collaborates with other teams to adopt Responsible AI practices and tooling, mentors junior engineers, and defines technical strategy. Requires experience in applying advanced ML methods to production systems, particularly in responsible technology, and familiarity with LLMs/VLMs in large-scale systems.

Manager II, Machine Learning Engineering for Homefeed Retrieval Modeling at Pinterest. This role involves leading a team of 8-9 ML engineers to set strategy, architecture, and roadmap for ML-based solutions in Homefeed retrieval. Responsibilities include owning retrieval sources, ML optimization engines, signal development, and forward-looking investments like generative retrieval. The role requires deep expertise in large-scale production recommender systems and leadership experience.

Engineering Manager I on Pinterest’s Growth AI Products team, leading a group of engineers building AI-led products and capabilities that drive top-of-funnel growth. The role involves shipping user-facing experiences and AI-powered content representation improvements, partnering closely with product, design, analytics and ML teams. Responsibilities include owning the team's roadmap, driving AI-led innovations, establishing launch readiness standards for AI-powered features, and improving team operating cadence using AI.

Staff Product Manager for GenAI Safety team, responsible for defining and driving product strategy for ensuring Pinterest's GenAI-powered systems are safe, fair, and trustworthy. This involves building proactive safety frameworks, partnering with engineering, policy, data science, and design to protect users, anticipating novel harms, red-teaming AI features, and translating policy into product requirements and model guardrails. The role also involves defining and tracking quantitative safety metrics, developing incident response plans, and anticipating emerging risks from new AI capabilities.

Engineering Manager for Pinterest's Agent Foundations team, responsible for architecting, scaling, and leading the development of foundational agent platform systems including serving, evaluation, and monitoring. The role involves technical leadership, team management, and partnering with product and research to define the future of agent experiences at Pinterest.

Staff Software Engineer to lead the backend architecture and implementation of a GenAI-powered Conversion Health agent. The role involves designing and implementing services, data flows, and retrieval layers for agents to reason over conversion data, evolving existing GenAI applications with prompt hardening, retrieval quality improvements, and evaluation/safety checks. It also includes designing connections with downstream ads products, structuring the measurement context layer into AI-consumable signals, and partnering with various teams to translate measurement pain points into agent skills. The role emphasizes leading an evolving GenAI culture, navigating ambiguity, codifying guardrails, and driving engineering velocity and measurement quality.

Machine Learning Engineer II at Pinterest focused on building and improving ML models for core product surfaces like Homefeed, Ads, Growth, Shopping, and Search. The role involves developing cutting-edge deep learning and ML technologies for personalization, using data-driven methods, and working with large-scale systems and stream data. The primary output is the improvement and deployment of ML models within the consumer product.

Senior Software Engineer role focused on building simulation environments and AI-driven tools for the CTV advertising ecosystem. The role involves designing systems to model auction dynamics, bidding strategies, and campaign outcomes, and developing AI agents to automate experimentation and de-risk ML model deployments. Experience with modern AI tools, probabilistic modeling, and adtech is required.

Senior Director of Product Management for Ads Quality at Pinterest. This role will own the end-to-end product vision and strategy for a technically sophisticated domain within advertising. The candidate will lead a team of 10-15 Product Managers, partnering with Engineering, Data Science, Machine Learning, Sales, and Go-to-Market teams to optimize Pinner experience, advertiser outcomes, and business growth. The role requires deep expertise in digital advertising and ML-powered products, and a proven track record of building and inspiring PM organizations.

Senior Product Manager for Enforcement Systems at Pinterest, owning product strategy for infrastructure that detects, reviews, and acts on unsafe content. Leads development of AI-native automation frameworks using LLMs and VLMs for enforcement decisioning, ensuring accuracy against policy intent. Drives a platform expanding beyond Trust & Safety into other company domains.

Product Manager for AI/ML solutions focused on merchant presence and shopping experiences on Pinterest, utilizing LLMs to identify and surface relevant merchants, aiming to increase Pinner discovery of new brands and help merchants build diverse audiences. The role involves defining, designing, and launching AI/ML-powered experiences, partnering cross-functionally, setting product vision, and identifying opportunities to advance personalization.

Staff Technical Program Manager for ML/AI Platform at Pinterest, focusing on leading strategic programs for ML/AI Platform, GenAI infrastructure, and Agent Platform. The role emphasizes an AI-First Execution Mindset, using GenAI for program execution, prototyping AI-augmented tools, applying AI governance, and driving complex technical decisions. The TPM will translate strategy into execution, shape roadmaps, build scalable processes, and ensure cross-functional alignment.

This role focuses on building production-grade GenAI-enabled analytics solutions by integrating enterprise data sources and establishing LLM pipelines with evaluation, observability, and guardrails. It involves designing data models, developing data pipelines, writing SQL, and defining best practices for GenAI in analytics engineering.

Staff Software Engineer focused on building and scaling the foundational platform for Pinterest's agent experiences. This includes agent serving, evaluation, monitoring, and tool calling infrastructure. The role involves defining technical direction, leading cross-functional teams, and synthesizing agent technology research.

This role focuses on embedding AI-native engineering within business functions (Marketing, Finance, Sales, HR, Legal) to identify and build AI-powered automation tools. The engineer will work end-to-end, from discovery and scoping to prototyping, launch, and iteration, utilizing agentic frameworks, tool-calling, and responsible AI practices. The role requires strong software engineering skills, hands-on experience shipping AI solutions, understanding of agentic AI systems, system design, data/security judgment, business acumen, and clear communication.

This role focuses on designing conversational experiences for a multi-agent AI-powered business assistant on Pinterest, targeting merchants and advertisers. The designer will lead strategy, improve prompt management, and collaborate with cross-functional teams to create cohesive AI-driven user experiences for business products.

Machine Learning Engineer II at Pinterest focused on developing and implementing ML models for user targeting and personalization to drive engagement and growth. The role involves building scalable ML pipelines, conducting A/B tests, analyzing data, and contributing to ML infrastructure, with an emphasis on leveraging AI tools for engineering practices.

Director of Product Management for Personalized Experiences at Pinterest, focusing on AI/ML-powered features for user discovery, curation, and shopping. This role involves defining product vision, strategy, and requirements, partnering with cross-functional teams to deliver scalable consumer products.

ML Platform Engineer to join a team at the intersection of sysops, systems programming, architecture, and large-scale deployments. The platform underpins a real-time bidding agent and ML training system that drive $100M+ in annual revenue. Focus on building a Kubernetes + Ray backend for model training pipelines, and defining the next generation of the training and serving stack.

Software Engineer to build simulation and AI capabilities for a CTV advertising platform. The role involves designing and implementing systems to model the CTV advertising ecosystem, developing AI-driven tools to accelerate ML system development, and using simulation to de-risk ML model deployments. The engineer will also define technical direction and mentor others.

Director of Machine Learning Engineering for the Growth organization at Pinterest. This role will define the long-term ML vision, strategy, and operating model to drive user and engagement growth. Responsibilities include overseeing multiple ML teams, partnering with leadership on strategy, defining ML architecture, building and developing teams, and acting as a thought partner. The role requires deep expertise in building and operating large-scale ML systems in production, leading multiple ML teams, and defining technical strategies.

Lead the team that builds the serving and deployment infrastructure for all AI/ML models at Pinterest, including ultra-high-performance C++ model inference engines and production GenAI & LLM model inference stacks.

Engineering Manager to lead a mobile and backend team focused on verticalized shopping experiences, leveraging generative AI to transform user inspiration into actionable, shoppable moments. The role involves owning the technical roadmap, driving an experiment-led culture, and building the necessary AI systems (harness, context, retrieval, prompt orchestration, evaluation, guardrails) for production-ready LLM applications. The focus is on integrating AI-driven personalization and recommendation systems to improve conversion rates and user satisfaction.

Manager II, Machine Learning-Search at Pinterest, leading a team responsible for major areas of the search engine, including indexing, ranking, query understanding, personalization, ML-based retrieval, shopping, videos, and infrastructure efficiency. The role involves innovative applications of NLP and Vision Models for query recommendations, multimodal search, agentic search, and query-based module generation. Requires experience leading large-scale production ML systems and applied ML experience.

Product Manager for AI/ML Personalization at Pinterest, focusing on driving the future of personalized experiences on the platform. This role involves defining, designing, and launching AI/ML-powered features for user discovery, curation, and shopping, partnering with Engineering, Data Science, and Design to deliver impactful products on high-traffic surfaces.

Staff Data Scientist at Pinterest focused on the Engagement Ecosystem. The role involves developing and productionizing ML frameworks for forecasting, recommendation, and causal inference, applying advanced ML and generative AI techniques to model complex interactions, and championing responsible AI use. Requires expertise in ML, causal inference, experimentation, and large-scale data environments, with a track record of influencing product decisions and mentoring junior scientists.

Manager II, Machine Learning Engineering for Core Engineering at Pinterest, focusing on search and recommendations for over 500 million users. The role involves leading a team of ML engineers, driving technical direction, strategic planning, and execution for large-scale, low-latency systems and state-of-the-art ML models that deliver significant impact to pinners and business metrics.

Machine Learning Engineer at Pinterest focused on building and improving ML models for various product surfaces like Homefeed, Ads, Growth, Shopping, and Search. The role involves using data-driven methods to enhance candidate retrieval and working with large-scale recommendation systems.

Machine Learning Engineer at Pinterest focused on building and improving ML models for various product surfaces like Homefeed, Ads, Growth, Shopping, and Search, leveraging deep learning and large-scale data to personalize user experiences.

Machine Learning Engineer focused on Monetization at Pinterest, building and improving ML models for various product surfaces like Homefeed, Ads, Growth, Shopping, and Search. The role involves developing cutting-edge deep learning and ML technology for personalization, leveraging data for candidate retrieval, and enhancing content understanding with LLMs. Experience with large-scale recommender systems, ads ranking, and big data technologies is required.

Machine Learning Engineer focused on personalization and monetization within the consumer domain, specifically for Pinterest's ad platform. The role involves building and improving ML models for various product surfaces, leveraging data for candidate retrieval, and enhancing content understanding with LLMs. It requires end-to-end experience with ML systems and a practical understanding of recommender systems or ad ranking.