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. Level: Individual Contributor Compensation: $60,000 – $125,000 Location: San Francisco, CA About the Role 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 __ We're building the future of human data for AI, and the quality of our output depends on how well we enable our contributors. As a Training Specialist, you'll design, develop, and deliver training materials that onboard and upskill our expert network — ensuring every contributor understands task requirements, quality standards, and best practices from day one. You'll work closely with Strategic Project Leads, Data Science, and Operations to close quality gaps quickly and at scale. What You'll Do - Design and deliver project-specific training collateral within tight timelines (often 24–48 hours) for new AI data labeling programs - Develop training materials — written guides, annotated examples, rubrics, and assessments — that translate complex technical task requirements into clear contributor instructions - Analyze learner performance data, error patterns, and quality issues to identify training gaps and design targeted interventions - Train and coach operations staff (SPLs, Ops Associates) on instructional design principles, feedback techniques, and quality assessment methods - Build reusable content templates, frameworks, and self-serve resources to maintain training consistency across projects and customers - Continuously track training effectiveness via quality metrics, completion rates, and satisfaction scores — and iterate quickly - Collaborate with Product and Engineering to surface tooling improvements that support contributor learning at scale Required Qualifications - 3+ years in instructional design, training, or technical content creation - Proven ability to simplify complex concepts for non-expert audiences - Experience developing training materials under tight timelines - Strong written communication and structured thinking - Data-driven: comfortable analyzing performance metrics to improve programs Preferred Qualifications - AI/ML background or strong understanding of AI training methodologies (SFT, RLHF, model evaluation) - STEM degree or technical fluency (CS, Data Science, or related field) - Experience with LMS platforms or annotation tooling (Scale, Labelbox, Prodigy, etc.) - Background in customer success enablement, sales enablement, or technical consulting