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.
Level: Individual Contributor
Compensation: $75,000 – $110,000
Location: San Francisco, CA
HumanSignal specializes in operationally complex, multimodal data collection and annotation — delivering the datasets that frontier AI research requires and remote workforce marketplaces can't. We own projects end-to-end, from scoping and protocol design through final delivery, running on-site and distributed expert workforces across 50+ knowledge domains, 30+ languages, and 75+ countries. Our work spans RLHF, evals, red-teaming, and custom multimodal data creation, all powered by Label Studio Enterprise and built on a foundation of rigorous quality workflows, ethical sourcing, and full data security. This role sits at the operational core of that delivery engine — responsible for ensuring our clients get the highest-quality data on time, every time.
This role is not for everyone. HumanSignal Services operates at the intersection of frontier AI research and large-scale human data delivery — and the work is fast, demanding, and unforgiving of dropped balls. You'll own complex, high-stakes data programs end-to-end, managing expert workforces, navigating shifting customer requirements, and holding quality and delivery timelines simultaneously. There is no playbook handed to you. You will build it, break it, and rebuild it better. If you thrive under pressure, take personal pride in operational excellence, and don't quit when a project gets hard — this is the role for you
What You'll DoThe day-to-day is intense by design. You'll juggle multiple programs at once, each with its own contributors, quality standards, and customer expectations. You'll make hard calls with incomplete information, hold contributors and vendors accountable, and find creative solutions to problems that don't have obvious answers. The expectation is simple: own the outcome, no excuses. High performers here grow faster than anywhere else in the industry. The bar is high — and that's the point.
What You'll Do- Own end-to-end execution of multi-million-dollar AI data programs, directly accountable for data quality, throughput, margins, and customer satisfaction
- Design and manage data pipelines from customer specifications through final delivery, including taxonomy design, quality frameworks, and incentive structures
- Manage and performance-manage 1,000+ distributed contributors — sourcing, vetting, training, and coaching domain experts at scale
- Serve as the primary client contact for AI lab researchers: deliver consistent reporting, anticipate needs, and identify opportunities for program expansion
- Run daily internal war rooms to stay ahead of quality issues, bottlenecks, and delivery risks
- Partner cross-functionally with Engineering, Product, and Growth to build and improve operational infrastructure
- Deploy AI automations and data-driven tools to improve output quality and pipeline efficiency
- 2–4+ years in consulting, finance, startups, or operationally intensive roles
- Strong analytical skills; proficiency in SQL or Python preferred
- Track record managing complex, cross-functional projects with measurable outcomes
- Entrepreneurial mindset; comfortable building from scratch in ambiguous environments
- Exceptional communication skills and client-facing presence
- Technical or STEM degree (CS, Data Science, Engineering, or related field)
- Experience managing distributed workforces or marketplace operations
- Exposure to AI data, RLHF, or model evaluation workflows
- Background in investment banking, private equity, or management consulting
HumanSignal is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. HumanSignal does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, genetic information, or any other characteristic protected by applicable federal, state, or local law. We are committed to working with and providing reasonable accommodations to individuals with disabilities.
Skills Required
- 2-4+ years in consulting, finance, startups, or operationally intensive roles
- Strong analytical skills; proficiency in SQL or Python preferred
- Track record managing complex, cross-functional projects with measurable outcomes
- Exceptional communication skills and client-facing presence
What We Do
HumanSignal (formerly known as Heartex) enables data science teams to build AI models with their company DNA. With the emergence of generative AI, it’s more important than ever to build highly differentiated models by guiding foundation models with proprietary data and human feedback. Creators of Label Studio, the most popular open source data labeling platform, HumanSignal enables data scientists to develop high quality datasets and workflows for model training, fine tuning and continuous validation. Today, the Label Studio open source community has more than 250,000 users who have collectively annotated more than 100 million pieces of data. Label Studio Enterprise is available as a cloud service with enhanced security, automation, quality review workflows, and performance reporting, used by leading data science teams including Bombora, Geberit, Outreach, Wyze, and Zendesk.
