- Location
- San Francisco, California · San Francisco, California, United States
- Department
- Human Data (Services)
- Seniority
- Manager
- Source
- Greenhouse
Description
The future of AI — whether in training or evaluation, classical ML or agentic workflows — starts with high-quality data.
At HumanSignal, we’re building the platform that powers the creation, curation, and evaluation of that data. From fine-tuning foundation models to validating agent behaviors in production, our tools are used by leading AI teams to ensure models are grounded in real-world signal, not noise.
Our open-source product, Label Studio, has become the de facto standard for labeling and evaluating data across modalities — from text and images to time series and agents-in-environments. With over 250,000 users and hundreds of millions of labeled samples, it’s the most widely adopted OSS solution for teams working on building AI systems.
Label Studio Enterprise builds on that traction with the security, collaboration, and scalability features needed to support mission-critical AI pipelines — powering everything from model training datasets to eval test sets to continuous feedback loops.We started before foundation models were mainstream, and we’re doubling down now that AI is eating the world. If you're excited to help leading AI teams build smarter, more accurate systems — we’d love to talk.
What You'll Do
- Translate customer outcomes into integrated delivery plans — milestones, dependencies, critical path, DRIs, definitions of done — and manage scope as engagements evolve
- Own delivery health end-to-end: maintain crisp status, surface risks early, and drive blockers to resolution so engineers stay focused on technical work
- Run tight cadences that hold teams accountable to outcomes without micromanagement; every open item has an owner and a due date
- Build durable delivery systems: single source of truth, action-item registers, risk registers, and playbooks that scale across the delivery org
- Draft regular customer updates (often daily), own live and async reporting, and maintain stakeholder confidence through proactive communication
- Identify automation opportunities and build AI-driven workflows to reduce operational overhead across engagements
- Partner closely with Product, Engineering, and Go-To-Market teams to continuously raise the bar on delivery excellence
Required Qualifications
- 8+ years in program/technical program management or delivery operations
- Track record managing complex, multi-stakeholder enterprise programs
- Metrics-driven: owns and reviews delivery health KPIs weekly (on-time milestone rate, blocker aging, schedule variance, etc.)
- Strong judgment under pressure; makes good decisions with incomplete information
- Confident presence with senior engineers and executive customer stakeholders
Preferred Qualifications
- Experience with enterprise AI or ML deployments
- Familiarity with enterprise IT procurement and security processes
- Background in startup ops, management consulting, or forward-deployed engineering
- Experience building lightweight operating systems for distributed teams
