PhD Engineer — Prompt Responses for AI Training

About OpenTrain

OpenTrain is the #1 platform for building careers in AI training and data labeling. The platform connects skilled contributors with projects that shape how AI systems learn, while helping freelancers consolidate work, build a unified portfolio, and grow a durable freelance career.

This role is posted through OpenTrain and staffed for OpenTrain. Creating an OpenTrain account is free and lets you discover projects, apply, and track your AI training work in one place.

About AI Training Work

AI training (data labeling and human feedback) is the human side of building modern AI: experts create and curate examples, write and rate model responses, and provide high-quality inputs that determine how models reason and perform. Much of this work is remote, flexible, and accessible to domain specialists who want to directly influence cutting-edge systems.

• Work shapes how state-of-the-art AI systems behave.
• Flexible, remote, and often part-time — a way to contribute technical expertise outside traditional product teams.

The Role

OpenTrain is recruiting PhD-level engineers (Electrical, Mechanical, or Chemical) to produce authoritative written responses, design realistic experimental scenarios, and evaluate model outputs. Your deliverables will be used as training and evaluation data to teach next-generation AI systems to reason about advanced engineering problems.

• Position type: Contractor, part-time.
• Location: Remote worldwide.
• Time commitment: 20+ hours per week.
• Language: English required.
• Data type: Text (prompt responses, ratings).
• Labeling tasks: Text generation and evaluation/rating.

What You'll Do

• Deliver authoritative written responses to complex engineering prompts in your discipline.
• Review and interpret scientific literature to provide contextually accurate, up-to-date insights.
• Design and document realistic experimental scenarios grounded in advanced engineering principles.
• Analyze data and interpret results to inform AI training datasets with quantitative rigor.
• Apply advanced calculus and quantitative methodologies to problem-solving tasks.
• Ensure clarity, accuracy, and completeness of all submissions following provided guidelines.
• Collaborate with project coordinators to refine prompt responses and improve output quality.

Requirements

Candidates must meet the core qualifications below. Submissions are expected to meet a "golden response" standard of accuracy and completeness.

• PhD in Electrical, Mechanical, or Chemical Engineering (required).
• Demonstrated expertise in calculus, data analysis, research methodology, and experimental design.
• Exceptional written and verbal communication skills; ability to convey complex concepts clearly.
• Strong literature review capabilities and experience synthesizing scientific knowledge.
• Proven ability to produce high-quality, editor-ready deliverables with attention to detail.

Helpful Background

Experience with or interest in AI, machine learning, or technology-driven projects is a plus but not required. Candidates who understand how model outputs are used in training and evaluation will move quickly in this role.

Compensation & Hours

This is a part-time contractor role with strong hourly compensation. Pay and time expectations are listed below; OpenTrain lets you see and manage projects and earnings in one place.

• Pay: $90 USD per hour (posted range $80–$90/hr).
• Minimum weekly time: 20+ hours.
• Contract type: Contractor / Part-time, remote worldwide.

How It Works / How to Apply

If you meet the requirements and want to help shape AI with your engineering expertise, apply through OpenTrain. Create a free OpenTrain account to view the project, submit your profile and credentials, and apply. Selected contributors will receive project-specific instructions, guidelines, and coordinator support.

• Create an OpenTrain account (free) and complete your profile.
• Provide proof of PhD and examples of technical writing or research when requested.
• Work as a contractor; follow project guidelines and collaborator feedback to produce "golden" responses.