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

Own renewals, commercial negotiations, upsell opportunities, and client retention for AI startup customers. Develop sales strategies and go-to-market playbooks for AI monetization and usage-based billing. Partner cross-functionally to address complex customer needs, engage founders and influencers, generate pipeline, and represent Stripe at industry events.

Conduct statistical analysis, causal inference, experimentation, predictive modeling, and machine learning using large datasets. Build data pipelines, dashboards, reports, and production models with Python or R, SQL, and Spark. Analyze fraud, financial crime, and business outcomes, communicate actionable recommendations, collaborate with multidisciplinary teams, and present findings to stakeholders.

Analyze Stripe data and experiments to generate insights, build metrics, dashboards, reports, data assets, and pipelines, and evaluate product and business decisions through analytics and A/B testing. The intern will collaborate with multidisciplinary teams, communicate findings, extend the metrics semantic layer, present recommendations, and support data-driven decision-making across the company.

Support global equity programs and financial reporting through accounting close activities, journal entries, reconciliations, variance analyses, technical accounting research, audit support, and internal controls. The role focuses on equity and stock-based compensation under ASC 505 and ASC 718, process automation, policy development, and cross-functional partnership across Finance, Tax, Legal, Treasury, and related teams.

Selected high school students or recent graduates complete a 12-week, full-time, in-person software engineering fellowship in San Francisco or Seattle. Fellows own scoped production engineering projects, write and test software, participate in design discussions and code reviews, collaborate with teammates, learn unfamiliar systems, and communicate progress. Candidates must demonstrate exceptional technical work, strong programming fundamentals, collaboration, adaptability, rigorous thinking, and clear communication.

Lead accounting strategy and execution for mergers, acquisitions, and subsidiary integrations. Responsibilities include business combination accounting, technical valuation oversight, policy alignment, financial close and reporting, internal controls, reconciliations, audit support, and strategic investment accounting. Partner with corporate development, tax, legal, finance, external providers, and unintegrated teams while managing complex integration programs, process improvements, risks, dependencies, and cross-functional decisions.

Drive expansion of Stripe Issuing and Treasury among existing users by identifying new use cases, building strategic account plans, leading complex sales opportunities, negotiating deals, and coordinating cross-functional teams through implementation and growth. Serve as a trusted advisor to executive, commercial, product, and technical stakeholders while informing product roadmaps, developing go-to-market playbooks, maintaining forecasts, and using data and AI tools to prioritize opportunities.

Lead expansion sales for Stripe Issuing and Treasury across existing customers. Build strategic account plans, identify new use cases, manage executive and technical relationships, lead discovery and negotiations, coordinate cross-functional implementation, and drive product adoption, activation, and revenue growth. The role also involves forecasting, developing go-to-market playbooks, using AI-supported workflows, and informing product strategy through customer feedback.

Build and operate production machine learning systems for recommendations, ranking, personalization, contextual bandits, and agent-based recommendations. Responsibilities include model development, feature and data pipelines, evaluation, deployment, monitoring, experimentation, and reliability improvements. The role partners with engineering, data science, product, marketing, and sales teams to translate business problems into measurable ML outcomes.

Analyze partner integration and operational data to identify trends, anomalies, bottlenecks, and root causes. Build data pipelines, models, dashboards, automation scripts, and operational tooling that improve efficiency, accuracy, monitoring, and scalability. Collaborate with engineering, product, and partner operations teams to translate operational challenges into technical solutions, reporting requirements, and process improvements.