Computer Science Expert (PhD)

Cashback24x7; India; Remote; INR 2,066,000 - 4,822,000; Part time

Job summary

Cashback24x7 seeks a Computer Science Expert (PhD) for a remote contractor role to support an AI training initiative. You'll produce authoritative explanations, review CS data, and craft golden responses to guide model learning. Strong publication or research background is valued, with excellent communication and collaboration in remote teams. Start immediately upon onboarding and contribute to high-quality training data.

Qualifications

• PhD in CS with foundation and advanced topics.
• Ability to explain complex CS concepts clearly.
• Experience publishing scientific/technical CS materials.
• Familiarity with CS sub-disciplines and diverse audiences.

Responsibilities

• Provide authoritative CS responses for AI training.
• Review CS data, questions, and solutions for accuracy.
• Develop explanations and justifications across CS topics.
• Collaborate with annotation leads to refine requirements.
• Create golden responses to guide model outputs.
• Document context behind answers for interpretability.

Skills

Strong communication

Analytical rigor

Academic publishing

Cross-disciplinary knowledge

Education

PhD in Computer Science

Job description

Job DescriptionRole Title: Computer Science Expert (PhD)Role Type: ContractorLocation: Remotemicro1 is engaging Computer Science Experts (PhD) to contribute their advanced subject-matter expertise to a customer's AI training initiative.

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

Produce authoritative, accurate, and well-explained responses to advanced computer science queries aimed at AI model improvement, emphasizing clarity and depth rather than rubric-based scoring.

Review and evaluate computer science data, questions, and solutions to guarantee accuracy, completeness, and current best-practice alignment.

Develop comprehensive explanations and justifications across a wide array of computer science concepts, spanning foundational and specialized areas of the field.

Collaborate with annotation leads and project managers to refine requirements and uphold high standards for response quality.

Create exemplary "golden responses" that set benchmarks for future model outputs, ensuring consistency and reliability in training data.

Document context and rationale behind answers to assist model interpretability and future annotation efforts.

Participate in remote discussions or workshops to clarify objectives and maintain alignment across the contributor community.

Preferred Qualifications

• PhD in Computer Science or a closely related field with robust expertise in both foundational and advanced topics.
• Proven ability to communicate intricate computer science concepts with precision in both written and verbal forms.
• Experience in developing, reviewing, or publishing scientific, technical, or educational computer science materials (such as research articles, curricula, industry reports, or peer reviews).
• Familiarity with multiple sub-disciplines within computer science (algorithms and theory, systems, artificial intelligence and machine learning, databases, computer networks, security, etc.) and the ability to adapt explanations for diverse audiences.
• Exceptional attention to detail with a commitment to analytical accuracy and methodological rigor.
• Experience with AI, data annotation, or digital content development projects is advantageous but not essential.
• Strong collaboration skills, particularly in remote or cross-functional 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.