Physicist, PhD

What you’ll do

• Data annotation: Accurately label and categorize physics problems, concepts, diagrams, experiments, and other relevant data
• Concept mapping: Connect key physics principles and establish relationships between different topics (e.g., mechanics, electromagnetism, thermodynamics) to help AI models grasp the structure of the subject
• Solution review: Analyze and verify AI-generated solutions to physics problems, identifying errors and offering clear feedback to improve model performance
• Content development: Help create well-rounded training datasets that span a variety of physics topics and difficulty levels

About the role

• Flexible workload — work from anywhere, on your own schedule
• High impact — your craft directly improves models used by top AI labs & Fortune 500 teams
• Clear ownership — know exactly what success looks like and have autonomy to deliver
• Growth potential — consistent high performers spearhead new programs and mentor incoming SMEs

Interview process

• Complete a screening with Zara, our AI interviewer in English, to learn more about your background and experience.
• Domain-specific Zara interview to assess your understanding of advanced physics principles, your ability to analyze complex processes, and your skill in applying theoretical frameworks to real-world scenarios.

About Labelbox

Labelbox builds the data engine that accelerates breakthrough AI. Our platform, expert services, and marketplace let teams iterate on data as nimbly as they iterate on code, enabling safer, smarter models in production. We’re backed by SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins, and trusted by leading research labs and enterprises worldwide.