Work Mode: Remote
Engagement Type: Independent Contractor
Schedule: Full-Time or Part-Time Contract

Language Requirement: Fluent English

Role :

Partners with leading AI teams to improve the quality, usefulness, and reliability of general-purpose conversational AI systems. These systems are used across a wide range of everyday and professional scenarios, and their effectiveness depends on how clearly, accurately, and helpfully they respond to real user questions.

In engineering-related contexts, conversational AI systems must demonstrate accurate applied reasoning, quantitative precision, and practical problem-solving aligned with real-world systems. This project focuses on evaluating and improving how models reason about and explain engineering concepts across multiple disciplines.

What You’ll Do

- Write and refine prompts to guide model behavior in engineering scenarios

- Evaluate LLM-generated responses to engineering-related queries for technical accuracy, applied reasoning, and completeness

- Conduct fact-checking and verify any technical claims using authoritative public sources and domain knowledge

- Annotate model responses by identifying strengths, areas of improvement, and factual or conceptual inaccuracies

- Assess clarity, structure, and appropriateness of explanations for different audiences

- Ensure model responses align with expected conversational behavior and system guidelines

- Apply consistent evaluation standards by following clear taxonomies, benchmarks,



and detailed evaluation guidelines

Who You Are

- You hold a PhD in Engineering or a closely related field

- You have deep expertise in one or more of the following sub-domains:

- Mechanical & Physical Systems Engineering

- Electrical, Electronic & Computer Engineering

- Chemical, Materials & Process Engineering

- Civil, Environmental & Infrastructure Engineering

- You have significant experience using large language models (LLMs) and understand how and why people use them

- You have excellent writing skills and can clearly explain complex engineering concepts

- You have strong attention to detail and consistently notice subtle issues others may overlook

- Experience reviewing or editing technical or academic writing

Nice-to-Have Specialties

- Experience with applied research, industry engineering workflows, or systems design

- Prior experience with RLHF, model evaluation, or data annotation work

- Experience teaching, mentoring, or explaining engineering concepts to non-expert audiences

- Familiarity with evaluation rubrics, benchmarks, or structured review frameworks

What Success Looks Like

- You identify technical inaccuracies, flawed assumptions, or incomplete reasoning in engineering-related model outputs

- Your feedback improves the rigor, clarity, and correctness of AI explanations

- You deliver consistent, reproducible evaluation artifacts that strengthen model performance

📌 Electrical Electronic Engineer (PhD) - Remote (Madrid)
🏢 YO IT CONSULTING
📍 Madrid