Top Tech Jobs & Startup Jobs in San Francisco Bay Area, CA

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.

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.

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 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.

Develop and prototype large-scale text-to-image generative models (Pinterest Canvas), collaborate on multimodal embeddings, collect and prepare visual training data (including RLHF and fine-tuning), ship models to production, publish research, and mentor junior researchers.

The Machine Learning Engineer will develop and improve ML models for product surfaces, build data processing pipelines, and leverage machine learning technologies in advertisements.

Design, build, and operate full‑stack and backend services to support Sales, Marketing, and Finance. Lead technical design and production deployment of GenAI/ML features, own SDLC, ensure observability and validation, partner with cross-functional teams, and mentor engineers to deliver business outcomes.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.