The San Francisco Compute Company

The San Francisco Compute Company

Chief of Staff to the CEO

San Francisco, CA · Exec

H1B sponsorship availableDetected 13 days ago
Machine LearningLeadership

About the role

  • This role combines strategy, operations, and execution, working closely with the CEO on the highest-impact priorities and decisions shaping the company's future.
  • This role requires a five days in-person presence in our San Francisco office.

Responsibilities

  • Serve as a trusted partner and thought partner to the CEO on strategy, prioritization, and critical business decisions.
  • Help identify organizational bottlenecks and ambiguous problems, structure them into actionable plans, and drive resolution with the right owners.
  • Build enough understanding of our business, market, financing, and deal dynamics to engage in strategic discussions and tradeoffs.
  • Strong communicator who can create alignment internally and represent the company externally when needed.
  • We're building the company which will de-risk the largest infrastructure build-out in history.

Requirements

  • Strong technical fluency and ability to engage with Engineering, GTM, and Product leaders on complex topics (AI/ML, infrastructure, architecture, etc.)
  • Experience operating in high-growth, P0-to-1 environments where priorities evolve quickly.

Compensation

  • Team members are offered a competitive salary along with equity in the company

Benefits

  • Team members are offered a competitive salary along with equity in the company
  • We offer competitive medical, dental, vision insurance for employees and dependents and cover 100% of premiums
  • We offer unlimited paid time off as well as 10+ observed holidays
  • We offer biological, adoptive, and foster parents paid time off to spend quality time with family

Company info

  • Represent the CEO in select internal and external conversations with customers, partners, and stakeholders.

This listing is sourced directly from The San Francisco Compute Company's careers page and normalized into a canonical job model.