Materials Science Tutor

1. Role Overview Mercor is partnering with a leading AI research organization to engage professionals with advanced expertise in materials science. This full-time position offers the opportunity to shape the next generation of AI systems by contributing deep scientific knowledge across a wide range of materials-related disciplines. As an AI Tutor – Materials Science Specialist, you will help train AI models to understand, reason, and generate accurate outputs in fields such as energy materials, semiconductors, nanomaterials, polymers, ceramics, and alloys. You will work closely with technical teams to annotate, evaluate, and improve AI model outputs while refining data tools and selecting challenging problems that drive model improvement. The work involves creating and evaluating text, audio, and video data, providing clear, detailed feedback to enhance the model’s understanding of materials science concepts. 2. Key Responsibilities - Use proprietary tools to label, annotate, and evaluate materials science–related data - Support the creation of high-quality datasets for advanced AI training - Collaborate with technical teams to develop and refine annotation systems and workflows - Analyze and solve problems across diverse materials science subfields to improve model reasoning and performance - Interpret evolving instructions and deliver accurate, consistent results under minimal supervision 3. Ideal Qualifications - Master’s degree or PhD in materials science, physics, chemistry, chemical engineering, or a closely related field - Deep expertise in one or more areas such as semiconductors, energy materials, nanomaterials, alloys, ceramics, biomaterials, or polymers - Strong command of written and spoken English in both professional and informal contexts - Skilled in research, data analysis, and use of scientific databases and digital resources - Excellent communication, critical thinking, and organizational skills - Ability to work independently and apply sound judgment to complex, technical challenges - Genuine interest in technological innovation and AI development 4. Preferred Background - Publications or patents demonstrating expertise in materials science, preferably with first-author research papers in peer-reviewed journals - Teaching or tutoring experience in scientific or technical subjects - Prior experience in AI data annotation or technical writing - Experience mentoring or guiding others in scientific research or materials analysis 5. Work Environment - Based in Palo Alto, CA (in-office, 5 days per week) or fully remote with strong self-management skills - U.S.-based applicants must reside outside of Wyoming and Illinois - Typical hours: 9:00am–5:30pm PST during training, then adjusted to your local timezone - Remote workers must use a personal computer that meets one of the following requirements: a Chromebook, a Mac running macOS 11 or newer, or a Windows PC running Windows 10 or newer - Reliable smartphone access is required 6. Compensation & Benefits - Competitive pay ranging from $90,000 to $200,000 annually for U.S.-based professionals, depending on experience and location - For international candidates, compensation ranges are available upon request - Access to medical benefits, subject to your country of residence - Supportive, high-impact environment focused on advancing AI and scientific innovation 7. Application Process - Submit your resume - Complete a 20-minute introductory interview - Selected candidates will move on to a focused materials science data evaluation exercise - Finalists will participate in a team discussion and review of their expertise - The full process typically concludes within one week 8. About Mercor Mercor is based in San Francisco, CA and specializes in recruiting experts for top AI labs. Our investors include Benchmark, General Catalyst, Peter Thiel, Adam D’Angelo, Larry Summers, and Jack Dorsey.