Materials Scientist / Engineer

Micro1; India; Remote; INR 5,174,000 - 11,642,000; Full time

Job summary

Cashback24x7 is seeking a Materials Scientist/Engineer for a remote contractor role. You will analyze experimental data, review literature, and structure datasets to support AI model training, with a focus on materials science and related engineering fields.

The role emphasizes clear communication of complex concepts, rigorous quality checks, and collaboration with a distributed team to deliver well-documented technical results.

Qualifications

• Advanced degree in a materials-related field with specialization.
• Experience interpreting experimental results and literature reviews.
• Ability to summarize complex data clearly in writing and verbally.

Responsibilities

• Analyze and interpret scientific data from experiments and literature.
• Conduct literature reviews to identify key advances and challenges.
• Annotate and structure datasets to support AI model training.
• Develop realistic materials engineering scenarios and case studies.
• Explain materials phenomena clearly in writing and speech.
• Review quality and accuracy of scientific deliverables.
• Collaborate remotely with other contributors using digital tools.

Skills

Analytical skills

Data interpretation

Technical writing

Communication

Education

MS or PhD in Materials Science & Engineering, Metallurgy, Mechanical Engineering, Chemical Engineering or related with materials specialization

Tools

Microscopy

Spectroscopy

Mechanical testing

Job description

Job Description

Role Title: Materials Scientist / Engineer

Role Type: Contractor

Location: Remote

micro1 is engaging Materials Scientists / Engineers to contribute their technical expertise to a customer's advanced materials project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Scope of Work

• Analyze and interpret scientific data from experimental results, technical datasets, and research publications in materials science and engineering.
• Conduct comprehensive technical literature reviews to identify key advances, methodologies, and challenges in materials characterization and related fields.
• Annotate and structure technical datasets with precise, detailed commentary and context to support AI model training.
• Develop realistic scenarios and case studies that represent practical applications and challenges within materials engineering, metallurgy, or related sectors.
• Provide clear, well-organized written and verbal explanations of materials phenomena, properties, and scientific reasoning.
• Review and assure the quality, consistency, and accuracy of scientific deliverables submitted for project milestones.
• Collaborate remotely with other scientific contributors, leveraging digital tools and documentation practices.

Preferred Qualifications

• MS or PhD in Materials Science & Engineering, Metallurgy, Mechanical Engineering, Chemical Engineering, or a related discipline with a materials specialization.
• Demonstrated expertise in materials characterization techniques (e.g., microscopy, spectroscopy, mechanical testing).
• Strong analytical skills and experience interpreting complex scientific data.
• Substantial experience conducting technical literature reviews and summarizing key findings.
• Proven ability to communicate complex technical concepts clearly, both in writing and verbally, to diverse audiences.
• Experience with quality assurance and review of scientific documents or datasets.
• Familiarity with remote collaboration tools and digital knowledge-sharing environments.

Compensation Structure

Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week.

Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.