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

Serve as the CEO’s operating leverage by representing him in meetings, making decisions on his behalf, managing calendar and travel, coordinating high-priority work, and organizing executive presentations. Build and improve AI-powered automations for executive support, manage cross-functional deck production, and handle miscellaneous tasks with strong follow-through, organization, and discretion.

Architects and implements government-specific versions of software platforms, adapting data pipelines, APIs, and analysis tools to federal infrastructure, security, and compliance requirements. Owns the full development lifecycle, collaborates with government stakeholders, troubleshoots integrations, and delivers reliable mission-critical systems. The role requires full-stack software engineering, data engineering, compliance expertise, customer communication, and pragmatic technical decision-making.

Leads cross-functional project tracking across hardware, software, manufacturing, launch, flight, and field deployment. Maintains project ownership, milestones, deadlines, obligations, and action items; briefs leadership; coordinates internal deliverables; analyzes balloon performance data; and ensures postmortems, process improvements, and documentation become durable organizational capabilities.

Design and own a system to scale balloon manufacturing by 100x. Collaborate with the CTO and R&D engineers to improve balloon performance and manufacturability, identify and resolve manufacturing issues, and train technicians on new procedures and tools. The role requires expertise in web handling and film converting machinery, mechanical CAD, physics, supplier collaboration, and industrial-scale thin-film processing.

Own go-to-market execution for an agentic weather product, driving customer acquisition, retention, product-led growth, viral features, monetization experiments, and customer discovery. The role involves cold outreach, design-partner recruiting, engagement analytics, pricing tests, landing pages, email campaigns, referral mechanics, and close collaboration with product and engineering to scale from early traction to thousands of customers.

Build and operate reliable tooling for continuous weather-model inference, including failure detection and recovery. Develop real-time pipelines for atmospheric observations, handling late or missing data, and create visualization tools for monitoring data processing and model runs. Collaborate with deep learning, backend, and frontend engineers while owning systems in production. The role emphasizes strong software engineering, debugging, learning ability, infrastructure thinking, and effective use of AI tools; machine learning experience is not required.

Build and operate reliable machine learning infrastructure for real-time weather forecasting. Responsibilities include research-to-production pipelines, inference scaling, cloud and on-premise compute strategy, upstream weather-data pipelines, data quality checks, monitoring, alerting, distributed training reliability, auto-recovery, and job scheduling. The role requires production ML systems experience and expertise with PyTorch, Docker, large datasets, memory management, compression, and network debugging.