Learning Designer

Mercor's mission is to organize human intelligence to power the AI economy. We're a leading AI data company, building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercor's APEX benchmark family measures AI's real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work, translating that expertise directly back into agents.

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:

1. 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
     

2. 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
     

3. 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