AI Hiring Platform · San Francisco
Mercor's mission is to organize human intelligence to power the AI economy. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development. Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $3 million a day.
Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.
About the Role
We're looking for a Learning Designer to build the instructional infrastructure that powers Mercor's human data operations – both for our internal teams and the thousands of talent experts who execute complex AI training tasks.
Your work will span three key areas:
Project-level instructional design:
Review and improve project guidelines, rubrics, and instruction documents to maximize clarity and task performance for our talent experts to complete data annotation and evaluation work
Transform complex task specifications into well-structured instructional materials that talent experts can follow accurately
Partner with project teams to identify where documentation gaps are causing quality issues and design solutions
Centralized learning academies:
Build centralized academy programs for complex data types related to post-training for LLMs
Create structured upskilling pathways that prepare talent experts for increasingly sophisticated project work
Develop assessments and certification frameworks that validate readiness for specific project types
Internal training systems:
Design and develop training curricula for internal Mercor employees across the full project lifecycle – from onboarding fundamentals to advanced client-facing skills
Build competency-based learning paths that progress from foundational concepts to applied expertise
Develop evaluation and certification systems to ensure consistent quality and skill development across teams
You'll be designing learning experiences that develop genuine expertise, whether that's teaching an SPL to run a client conversation or helping a talent expert understand the nuances of turning their expertise into a rubric that can evaluate LLM responses. Your work directly impacts the quality of data that trains frontier AI systems.
What We're Looking For
2+ years of experience in learning design, instructional design, curriculum development, or technical writing
Strong pedagogical foundation – you understand how people actually learn and can design experiences that build real skills, not just surface familiarity
Excellent writing and communication skills – you can make complex concepts clear and actionable for diverse audiences
Experience creating task documentation or procedural guides – you know how to write instructions that people can actually follow
Ability to diagnose instructional problems – when task quality suffers, you can identify whether it's a training gap, a documentation issue, or something else
Experience creating multi-format content (written documentation, video, interactive exercises, assessments)
Comfort with ambiguity and rapid iteration – we're building systems in a fast-moving environment, and you'll need to ship and improve continuously
Systems thinking orientation – you see how individual skills connect to broader operational excellence
Nice to Have
Experience in tech, AI/ML, or data operations environments
Experience building training programs at high-growth startups
Background in teaching, coaching, or educational leadership
Familiarity with data annotation, labeling, or evaluation workflows
Background in training for client-facing or sales roles