Neuroscience Quality Assurance Lead

Overview

This is a remote contractor position for a Neuroscience Quality Assurance Lead focused on neuroscience and cognitive science AI training work. The role centers on maintaining quality, consistency, and reviewer performance across scientific content projects that support AI model training.

You will assess AI-produced neuroscience and cognitive science material, review trainer and QA output, and make sure all work meets the required standards for accuracy, clarity, formatting, instruction adherence, and project-specific rubrics. The role calls for strong subject matter knowledge, careful judgment, polished written communication, and the ability to coordinate quality processes with distributed expert teams.

The hiring process includes an AI interview, a task based on the domain, and a conversation with a recruiter. There is no active project available immediately for this role, but suitable candidates may be contacted first when matching opportunities open up and may also gain access to future work through the expert network.

What the role involves

You will review neuroscience and cognitive science outputs for scientific correctness, conceptual precision, evidence awareness, ethical sensitivity, and readability. In addition to checking the work itself, you will help keep contributors aligned by sharing updates, clarifying guidelines, maintaining reference materials, and supporting onboarding and activation efforts.

Quality focus areas

• Check outputs for scientific accuracy, precise terminology, and sound interpretation of research.
• Review claims for weak logic, unsupported causation, overstatement, neuromyths, and misleading clinical implications.
• Assess understanding of neural systems, cognition, perception, memory, learning, language, decision-making, and brain-behavior relationships.
• Verify instruction-following, formatting, clarity, and consistency with rubrics.
• Watch for ethical concerns and pseudoscientific or overly confident statements.

Team and workflow support

• Give written feedback to trainers and QAs and escalate repeated or serious quality issues.
• Communicate project changes, review standards, and workflow updates through remote collaboration tools.
• Answer questions about experimental design, statistical interpretation, neural mechanisms, and related topics.
• Track inactive contributors, encourage re-engagement, and note availability concerns.
• Build and maintain documentation such as style guides, FAQs, trackers, examples, honeypots, calibration tasks, and onboarding resources.
• Run onboarding or training sessions to explain expectations, workflows, and review standards.
• Recommend process improvements that make the QA workflow more scalable and reliable.

Selection process

Candidates move through an AI-based interview, a subject-specific task, and a recruiter interview before final consideration.

Additional information

This is described as an hourly remote contractor position. It is connected to a fast-growing AI data services company that supports major AI companies and foundation model labs. The work contributes to improving AI systems by helping ensure scientific training data is accurate, careful, ethically appropriate, and clearly explained.