About HumanSignal
Real-world data is the competitive edge in AI.
HumanSignal is a human data partner for companies building AI models and products. Our customers ship better AI, faster, because we partner with their researchers from real-world data creation to annotation to delivery.
We design and create datasets from scratch, recruit and manage the domain experts who evaluate model output, and run everything through our own platform, Label Studio, the open-source standard for data labeling and evaluation, used by over 1 million practitioners worldwide.
We specialize in the operationally complex: real-world data collection, multimodal pipelines, and multi-step workflows. Advanced ML and AI teams use our enterprise platform to run their own data factories, and our services team to extend their reach where in-house capacity runs out.
If you want to do work that materially shapes how the next generation of AI products gets built, 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