Computer Specialist
Overview:
We are looking for a Computer Science Expert to review, validate, and refine prompt-based questions designed to train AI tutors. Your expertise in algorithms, data structures, operating systems, databases, theory of computation, and software design will ensure each prompt and response is technically accurate, educationally impactful, and reflective of real-world computing applications.
Prompt & Response QA:
• Review AI-generated prompts and responses for accuracy, clarity, and pedagogical value.
• Tag prompts with metadata (e.g., topic area, difficulty, programming language).
• Rewrite or refine responses in a step-by-step, tutor-style voice to improve learner understanding.
Code & Concept Verification:
• Run and validate code snippets, algorithm traces, and data structure manipulations to confirm correctness.
• Identify issues in logic, performance, syntax, or conceptual depth, and propose improvements.
Scenario Analysis:
• Evaluate real-world-inspired prompts (e.g., database query optimization, memory management in OS, graph traversal for social networks) for relevance and challenge level.
Research & Cross-Checking:
• Reference trusted sources like CLRS (Introduction to Algorithms), Database System Concepts, CS50 materials, and official programming documentation to ensure correctness.
Structured Feedback:
• Provide well-organized, constructive feedback explaining any technical or instructional revisions.
• Emphasize clarity, logical soundness, and alignment with undergraduate CS learning outcomes.
Quality Monitoring:
• Ensure each prompt-response pair effectively tests computer science fundamentals, programming skills, and reasoning ability.
Ideal Qualifications:
• Computer Science Expertise: Strong knowledge of core CS topics, including programming, complexity theory, software engineering, and computer systems.
• Analytical Problem-Solving: Able to verify solutions, debug code, and detect flaws in algorithmic logic.
• Educational Communication: Skilled in breaking down CS concepts in a clear, student-friendly manner.
• Attention to Detail: Able to catch off-by-one errors, semantic mistakes, or misinterpreted constraints.
Minimum Qualifications:
• Master’s degree or PhD in Computer Science or a closely related field.
• 2+ years of experience in software engineering, computer science research, or teaching.
• Proficiency in one or more programming languages (e.g., Python, Java, C++, JavaScript).
• Experience with educational or technical writing is preferred.
Additional Details:
• Remote and asynchronous work — set your own hours.
• ~20 hours of work over a one-week period.
• Must be based in the U.S. or Canada.
• Clear expectations and structured workflow provided.
Application and Onboarding Process:
• After submitting your resume, you’ll complete a brief 10-minute session with our AI interviewer to assess your research and reasoning skills.
• If selected, we’ll follow up with next steps and onboarding details within a few days.
About Mercor:
• Mercor is a San Francisco-based team specializing in connecting top experts with leading AI research projects.
• Our investors include Benchmark, General Catalyst, Adam D’Angelo, Larry Summers, and Jack Dorsey.
Overview:
We are looking for a Computer Science Expert to review, validate, and refine prompt-based questions designed to train AI tutors. Your expertise in algorithms, data structures, operating systems, databases, theory of computation, and software design will ensure each prompt and response is technically accurate, educationally impactful, and reflective of real-world computing applications.
Prompt & Response QA:
• Review AI-generated prompts and responses for accuracy, clarity, and pedagogical value.
• Tag prompts with metadata (e.g., topic area, difficulty, programming language).
• Rewrite or refine responses in a step-by-step, tutor-style voice to improve learner understanding.
Code & Concept Verification:
• Run and validate code snippets, algorithm traces, and data structure manipulations to confirm correctness.
• Identify issues in logic, performance, syntax, or conceptual depth, and propose improvements.
Scenario Analysis:
• Evaluate real-world-inspired prompts (e.g., database query optimization, memory management in OS, graph traversal for social networks) for relevance and challenge level.
Research & Cross-Checking:
• Reference trusted sources like CLRS (Introduction to Algorithms), Database System Concepts, CS50 materials, and official programming documentation to ensure correctness.
Structured Feedback:
• Provide well-organized, constructive feedback explaining any technical or instructional revisions.
• Emphasize clarity, logical soundness, and alignment with undergraduate CS learning outcomes.
Quality Monitoring:
• Ensure each prompt-response pair effectively tests computer science fundamentals, programming skills, and reasoning ability.
Ideal Qualifications:
• Computer Science Expertise: Strong knowledge of core CS topics, including programming, complexity theory, software engineering, and computer systems.
• Analytical Problem-Solving: Able to verify solutions, debug code, and detect flaws in algorithmic logic.
• Educational Communication: Skilled in breaking down CS concepts in a clear, student-friendly manner.
• Attention to Detail: Able to catch off-by-one errors, semantic mistakes, or misinterpreted constraints.
Minimum Qualifications:
• Master’s degree or PhD in Computer Science or a closely related field.
• 2+ years of experience in software engineering, computer science research, or teaching.
• Proficiency in one or more programming languages (e.g., Python, Java, C++, JavaScript).
• Experience with educational or technical writing is preferred.
Additional Details:
• Remote and asynchronous work — set your own hours.
• ~20 hours of work over a one-week period.
• Must be based in the U.S. or Canada.
• Clear expectations and structured workflow provided.
Application and Onboarding Process:
• After submitting your resume, you’ll complete a brief 10-minute session with our AI interviewer to assess your research and reasoning skills.
• If selected, we’ll follow up with next steps and onboarding details within a few days.
About Mercor:
• Mercor is a San Francisco-based team specializing in connecting top experts with leading AI research projects.
• Our investors include Benchmark, General Catalyst, Adam D’Angelo, Larry Summers, and Jack Dorsey.
