Chemistry & Materials Science - AI Trainer

Job Title: Chemistry & Materials Science - AI Trainer

Job Type: Part-time, Paid per task

Location: Remote

Job Summary:

Join our customer's team as a Chemistry & Materials Science - AI Trainer and play a pivotal role in shaping the next generation of AI-driven scientific solutions. You will leverage your technical expertise to evaluate, enhance, and create robust training data and guidelines for chemistry and materials science applications. This is a unique opportunity to impact the development of cutting-edge AI technology in a highly collaborative and intellectually stimulating environment.

Key Responsibilities:

• Assess AI-generated responses related to chemistry, materials science, experimental techniques, and scientific research.
• Develop structured training datasets, scientific prompts, experiment scenarios, and clear technical explanations.
• Detect inaccuracies or gaps in AI output and recommend precise improvements to ensure scientific validity.
• Collaborate closely with AI research teams to refine content guidelines and quality standards.
• Promote adherence to laboratory safety, ethical guidelines, and best practices in all AI training materials.
• Interpret complex experimental data and convey findings in accurate, accessible formats.
• Support continuous improvement of AI models by providing expert feedback and domain insights.

Required Skills and Qualifications:

• Bachelor’s, Master’s, or PhD in Chemistry, Materials Science, Chemical Engineering, or a related field.
• Minimum 3 years of hands-on experience in laboratory instrumentation, materials synthesis, or characterization techniques.
• Expertise in scientific data interpretation, analysis, and technical writing.
• In-depth knowledge of laboratory methodologies, safety protocols, and research ethics.
• Exceptional written and verbal communication skills, with a keen attention to clarity and detail.
• Ability to critically evaluate scientific content and translate complex concepts for diverse audiences.
• Demonstrated commitment to accuracy, scientific rigor, and continuous learning.

Preferred Qualifications:

• Experience using computational modeling tools, materials simulations, or computational chemistry software.
• Background in advanced fields such as polymer science, nanotechnology, catalysis, or metallurgy.
• Previous involvement with interdisciplinary or AI-driven scientific projects.