Computer Science Expert (PhD)

About micro1

micro1 is a data engine that helps AI labs train foundational models and enterprises build AI agents. We provide frontier evaluations and reinforcement learning environments used to improve LLM capabilities, as well as contextual evaluations used to monitor and improve AI agents in enterprise settings. Our data engine includes an AI recruiter agent that sources and vets domain experts, a data platform that enables rapid production of high-quality training data, and a pipeline performance system that ensures both quality and velocity.

Our goal is to have 1 billion people doing meaningful work by contributing their expertise to the development of frontier AI models. We’ve raised $40M+ in funding, and our AI recruiter has powered more than 1 million AI-led interviews as our global network of experts expands to form the human intelligence layer for AGI.

Position

micro1 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.

Your qualification

• 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.

Additional details

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.