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

As an Engagement Marketing Manager, you'll lead customer activation and habituation strategies, run experiments, collaborate cross-functionally, and drive growth using data analysis and AI tools.

Design, build, and operate high-throughput, fault-tolerant ledger and settlement systems of record. Develop durable ledgering APIs, settlement orchestration, and treasury automation. Ensure data contract integrity for downstream finance, run production systems to SLOs, debug multi-layer issues, lead and mentor engineers, and use AI tooling to reduce operational toil.

Lead end-to-end data science for lending products: define measurement frameworks, analyze experiments and cohorts, evaluate risk and model performance, use AI tools to accelerate analysis, build reusable tooling, and mentor junior scientists while partnering with product, engineering, and risk stakeholders.

As a Senior Software Engineer on the Cash App Banking team, you will lead the design, execution, and delivery of banking features, collaborating across teams to enhance the user experience.

Design, deploy, and maintain end-to-end ML risk solutions at scale to detect and prevent fraud, merchant risk, and credit loss. Partner with cross-functional teams, lead technical decisions, build ML tooling, monitor models in production, and investigate emerging abuse patterns to improve detection and decisioning.

Looking for a Software Engineer to build financial products and tooling for Cash App's Lending team, ensuring quality and compliance while collaborating across domains.

The Senior Technical Account Manager will act as a technical partner to Cash App Pay and Afterpay merchants, optimizing integrations and ensuring growth through collaboration and technical solutions.

Senior individual contributor building and maintaining underwriting and credit decisioning ML systems for Cash App Borrow and Afterpay. Responsibilities include feature engineering, model training, calibration, experimentation, deployment, monitoring, and portfolio-level analysis. Collaborate with cross-functional teams to align models with business and regulatory goals and develop AI-native engineering workflows and governance for reliable, auditable model development.