Job Description
- Job Description:
- Develop and refine prompts to guide AI behavior in engineering-specific scenarios
- Evaluate model-generated responses for technical correctness, applied reasoning, completeness, and practical relevance
- Fact-check technical claims using authoritative public sources and domain expertise
- Annotate outputs by identifying conceptual gaps, flawed assumptions, and factual inaccuracies
- Assess clarity, structure, and appropriateness of explanations for various audiences
- Ensure responses align with expected conversational standards and system-level guidelines
- Apply structured evaluation frameworks, taxonomies, and benchmarking standards consistently
- Requirements:
- PhD in Engineering or a closely related field
- Deep expertise in one or more of the following domains:- Mechanical & Physical Systems Engineering- Electrical, Electronic & Computer Engineering- Chemical, Materials & Process Engineering- Civil, Environmental & Infrastructure Engineering
- Strong familiarity with large language models (LLMs) and their practical applications
- Excellent written communication skills with the ability to clearly explain complex technical concepts
- High attention to detail and ability to detect subtle technical inaccuracies
- Experience reviewing, editing, or critiquing technical or academic writing
- Applied research, industry engineering workflows, or systems design (preferred)
- Experience with reinforcement learning from human feedback (RLHF), model evaluation, or structured data annotation (preferred)
- Teaching, mentoring, or explaining engineering concepts to non-expert audiences (preferred)
- Familiarity with structured evaluation rubrics, benchmarks, or quality assurance frameworks (preferred)
Benefits:
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