Remote

We are sharing a specialised part-time consulting opportunity for experienced electrical engineering professionals with backgrounds in STEM problem review, graduate-level engineering verification, scientific reasoning, technical evaluation, grading methodology, and structured quality assurance. This role supports current and upcoming remote consulting opportunities focused on AI-assisted STEM training data review, electrical engineering problem evaluation, simulated research environment assessment, ground truth verification, grading rubric review, and high-quality project execution. Selected professionals will review complex STEM prompts, verify expert-level answers, assess model-generated reasoning trajectories, and provide detailed feedback based on electrical engineering expertise and scientific judgment., Professionals in this role may contribute to: Electrical Engineering Problem Review

• Review complex STEM and electrical engineering problem prompts for clarity, technical rigor, completeness, and suitability as training data
• Independently verify ground truth answers for graduate-level electrical engineering problems
• Evaluate whether task prompts require appropriate domain reasoning, clear assumptions, and technically sound solution paths
• Identify ambiguous wording, missing constraints, incorrect assumptions, incomplete derivations, or weak problem construction

Ground Truth & Grading Quality Evaluation

• Assess golden answers for correctness, completeness, mathematical rigor, and alignment with the stated task requirements
• Review grading criteria for robustness, objectivity, and consistency across acceptable solution approaches
• Determine whether evaluation rubrics properly capture correct reasoning, valid alternatives, numerical tolerances, and common error cases
• Provide Accept, Revise, or Reject verdicts with concrete written explanations

Simulated Research Review

• Assess simulated research environments for scientific realism, construction quality, and diversity
• Review seed prompts and multi-agent trajectories to evaluate whether research-style workflows are plausible and technically meaningful
• Read and summarize model agent rollouts, including stronger and weaker solution attempts
• Identify issues related to unrealistic reasoning, weak scientific setup, poor trajectory diversity, or insufficient domain grounding

Structured Feedback & Quality Control

• Provide clear written feedback explaining electrical engineering reasoning, grading concerns, task-quality issues, and suggested improvements
• Follow standardized review forms, detailed task instructions, and project-specific quality criteria accurately
• Review discrete STEM QA deliverables within expected timelines
• Collaborate through asynchronous project workflows to improve technical training data quality and AI-assisted STEM evaluation outputs, * Apply electrical engineering expertise to structured remote STEM quality review work
• Contribute to high-quality AI-assisted technical evaluation and training data development
• Use graduate-level engineering judgment in a focused review and quality-control environment
• Work on discrete deliverables aligned with subject-matter expertise and availability
• Remote structure with competitive compensation

Contract Details

• Independent contractor role
• Fully remote part-time project work
• Expected workload is approximately 2.5 reviews per week, with each review typically requiring 2-4 hours depending on task complexity
• Initial engagement may run for approximately three weeks depending on project timeline, onboarding status, and project needs
• Work may be structured around STEM QA review, simulated research review, ground truth verification, grading methodology assessment, or task-based assignments
• Review windows may include time-limited problem access, with extensions depending on project rules and availability
• Professionals may be able to select problems aligned with their domain expertise depending on project structure
• Competitive rates of up to $85 USD per hour depending on electrical engineering expertise, review quality, and project scope
• Screening may include resume or academic background review, domain alignment assessment, and a brief technical or sample review task
• Weekly payments via Stripe or Wise
• Projects may be extended, shortened, or adjusted depending on scope and performance
• Work will not involve access to confidential or proprietary information from any employer, client, vendor, or institution
• Please note: We are unable to support H1-B or STEM OPT candidates at this time

About the Platform This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams. By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: .

• MS or PhD in electrical engineering or a closely related technical field
• Strong ability to independently verify ground truth solutions for graduate-level electrical engineering problems
• Experience reviewing technical problems, grading methodologies, solution explanations, model outputs, or structured STEM tasks
• Strong scientific reasoning and ability to evaluate technical correctness, methodological soundness, and problem clarity
• Ability to summarize complex model-generated reasoning trajectories clearly and objectively
• Strong attention to detail and ability to identify subtle errors in reasoning, assumptions, calculations, or grading logic
• Comfort reviewing AI-generated STEM content and applying detailed evaluation criteria
• Excellent written communication skills
• Ability to work independently in a remote, asynchronous, project-based environment

Nice to Have

• Advanced expertise in one or more electrical engineering subdomains, such as circuits, signal processing, control systems, power systems, electromagnetics, communications, semiconductor devices, embedded systems, or related areas
• Experience teaching, grading, reviewing, or designing graduate-level electrical engineering problems
• Familiarity with rubric-based review, benchmark evaluation, technical QA, research-style assessment, or structured feedback workflows
• Experience evaluating multi-step mathematical solutions, simulation-based reasoning, symbolic derivations, or numerical verification
• Ability to provide concise, actionable feedback for both technical correctness and training data quality