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

Provide securities law counsel for a public company: prepare and file SEC reports (10-K, 10-Q, 8-K, registration statements), support proxy and shareholder meeting logistics, advise on insider trading/Rule 10b5-1 and Section 16 filings, review external communications for Regulation FD compliance, monitor securities law developments, train employees, and support corporate governance matters.

Build and operate Go-based backend services and APIs to manage hardware lifecycle (RMA, data center operations, node repairs). Design scalable, reliable microservices, integrate vendor APIs, manage databases for operational and reporting use cases, and deploy/operate services on container platforms.

Design, build, and operate large-scale data ingestion, storage, and query systems for AI/ML experiment tracking. Architect and optimize distributed backend services (petabyte-scale), implement customer-facing APIs, run services on Kubernetes/cloud, diagnose production issues, lead architectural initiatives, and mentor junior engineers.

Own post-sales technical relationships for a small portfolio of strategic enterprise customers. Drive incident triage and remediation, deliver proactive architectural guidance and cost optimization, scope and orchestrate Vercel engagements, represent the customer internally, and ensure TAM engagement renewals and customer success metrics.

Build and maintain scalable, reliable ML data platform systems to support dataset generation, model training, analytics, monitoring, and large-scale inference. Collaborate with ML, software, and infrastructure engineers to design cost-efficient data lake and training infrastructure using vendor and open-source tools to enable next-generation ML models.

Lead end-to-end brand and product launch projects, own video production and shoots, manage scope/budgets/schedules, build timelines and creative workflows, manage agency relationships, and partner cross-functionally to deliver high-volume, multi-workstream creative assets on time.

The Sales Engineer will support Account Executives by aligning Superhuman's solutions with educational institutions’ needs, delivering demos, conducting POCs, and engaging with technical stakeholders.

Serve as primary Technical Account Manager post-go-live for enterprise life-science customers, driving adoption, managing Optimization Services Success Packages, delivering sprint-based accelerators, owning account escalation, project plans, and stakeholder relationships across scientists, R&D leaders, and IT.

Lead and scale executive communications for the Office of the President, build a company-wide executive comms program, translate complex technical topics for varied audiences, integrate generative AI into workflows, prepare and coach the executive for appearances, craft keynotes/op-eds/internal and external messaging, and collaborate cross-functionally with PR, IR, and employee communications.

Support Sales by developing campaign strategies, conducting market and trend analysis, gathering client requirements, creating presentations, analyzing data to generate insights, optimizing campaign delivery, identifying upsell opportunities, and collaborating with cross-functional teams to drive new business growth and client success.

Lead strategic sourcing and supplier management for corporate services. Partner with HR, Facilities, Legal, Finance, InfoSec, and others to run RFx events, negotiate commercial terms, manage supplier performance, reduce risk, and deliver measurable savings and cost avoidance while enabling timely business decisions.

Lead product launches and long-term adoption programs for core Notion features. Partner with Product, Design, Engineering, Sales and Marketing to shape messaging, competitive positioning, release communications, sales enablement, and lifecycle campaigns that drive awareness and sustained feature adoption.

Manage a book of ~40 mid-market accounts to drive new sales and expansion. Own quota ($2-4M), lead cross-functional deal teams, build executive relationships, qualify and close complex multi-threaded SaaS deals using outcome-based selling (MEDDPICC), forecast pipeline, price and negotiate contracts, collaborate with channel/marketing/product/customer success, and occasionally travel for customer meetings and team events.

As a Manager in Data Science, you'll lead the development of machine learning models, partner with engineering and product teams, and analyze large datasets to enhance customer experiences and prevent fraud.