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

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.

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.

Design and implement scalable AWS-based data infrastructure using Spark and Scala. Build fault-tolerant batch and streaming pipelines, optimize storage formats and engines, collaborate with Data Science and Product, implement automated data quality checks, and deliver performant data assets and APIs.

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

Lead strategy, technical development, and execution of Pinterest's billing systems. Expand and automate billing capabilities, design internal and external billing UIs, support new geographies and payment methods, collaborate cross-functionally, and use data and AI to drive measurable product and workflow improvements.

Lead architecture and strategic direction for Pinterest's data warehouse, analytics tools, and data governance. Drive cross-functional initiatives to build scalable data platforms, AI-assisted pipeline tooling, and analytics capabilities. Mentor engineers, define policies and tooling, and deliver measurable adoption and business impact across the company.

Lead cross-functional Monetization Data Science programs to build a trusted SSOT, instrumentation, production data pipelines, and self-serve analytics. Drive automation, monitoring, governance, and input-metrics cadences, run deep-dive analyses, and embed AI-first workflows and safety-by-design for scalable decision-making and reduced operational toil.

Design, build, and operate backend services and large-scale distributed systems powering Pinner-facing features. Partner with product, design, and data teams to implement GraphQL APIs, convert REST to GraphQL, improve developer productivity, employ automated testing and A/B experiments, and leverage AI to accelerate and validate engineering work from prototype to production.

Lead strategic direction and product vision for complex AI-native consumer features, set design quality and system standards, drive major design initiatives, mentor and grow design talent, and collaborate cross-functionally to bridge vision and execution.

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.