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

Owns internal IT operations, including employee support, onboarding and offboarding, application provisioning, endpoint management, identity and access, SaaS administration, and office technology. The role audits and improves security controls, standardizes IT workflows, cleans up accounts and permissions, manages devices, and automates repetitive processes. It requires independent ownership, strong communication, and practical security judgment while supporting a technical engineering organization in an onsite startup environment.

Lead 0-to-1 product and brand design for Inferact and vLLM: create visual identity, high-impact launch assets, and developer-facing product UX. Establish design systems, collaborate with founders and engineers, and iterate on web surfaces, internal tooling, and enterprise product interfaces.

Lead Inferact’s legal function as its first in-house lawyer. Own commercial contracting, technology licensing, partnerships, vendor and customer agreements, and general corporate legal matters. Build legal processes, manage outside counsel, advise leadership and technical teams, and address open-source licensing, privacy, export controls, and emerging AI regulation. The role requires hands-on legal execution while scaling a legal function for a fast-growing AI infrastructure company.

Own and scale People Operations and HR infrastructure across the employee lifecycle. Responsibilities include onboarding, payroll, benefits, employee relations, compliance, HR systems, and immigration and visa workflows. The role partners with leadership, finance, engineering, employees, vendors, and external legal counsel while building scalable processes for a growing AI startup.

Lead product marketing and go-to-market for vLLM: own conferences, partner events, landing pages, speaker coordination, collateral, and community programs. Shape messaging, build partner relationships, and execute developer-focused campaigns in collaboration with product, engineering, design, and leadership.

Lead and scale a senior ML systems engineering organization focused on inference: recruit and develop specialized talent, translate research into execution, ensure high-performance inference across models, hardware, and deployments, and maintain technical rigor and operational excellence.