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

Develop and maintain backend infrastructure for an AI-powered wealth management platform. Collaborate with frontend teams and architect distributed systems.

The Senior Sales Engineer will partner with Account Executives to lead technical discovery, tailor demos, and ensure customer satisfaction through technical support and solution mapping. Responsibilities include demonstrating product value, educating customers, and providing feedback to improve product development.

The Corporate Project Manager will lead projects from initiation to closing, managing resources, defining scope, budget, and facilitating teams for successful project deliverables.

Lead Copper's end-to-end hardware quality: build quality systems, drive supplier and factory performance, own assembly and field failure analysis, enable NPI quality readiness, and establish feedback loops and processes while defining and growing the quality team.

The role involves developing and managing partnerships in the consumer payments sector, focusing on on-chain payment integrations and fostering ecosystem growth.

The Senior/Staff Systems Engineer will lead technical design discussions, prototyping, and integration of software and hardware for a medical robot, contributing to safety and clinical applications.

Build core infrastructure for a durable application runtime: implement schedulers, runtimes, and data plane components in Rust; optimize cluster scheduling, resource utilization, and performance; extend SDKs; collaborate across product and engineering from research to production.

The Sales Representative engages with inquiries about insurance, provides virtual consultations, generates quotes, and completes the sales cycle within 72 hours.

The Founders Associate Intern will assist the CEO in executing strategy, managing projects, conducting research, preparing reports, and streamlining processes within the company.

Develop and deploy state-of-the-art computer vision models for medical imaging, focusing on training vision encoders for radiology applications and evaluating model performance across multiple modalities.