
Engineering (Coding) Subject Matter Expert - AI Evaluation (US-Remote)
Department:Software Engineer
Type:REMOTE
Region:Austin, TX
Location:Austin, Texas Metropolitan Area
Experience:Entry level
Estimated Salary:$80,000 - $120,000
Skills:
ENGINEERINGCODINGGENAILLMPROMPT ENGINEERINGAIDATA COLLECTIONEVALUATIONRESEARCHFACT-CHECKINGBIAS MITIGATIONCONTENT DEVELOPMENT
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Job Description
Posted on: November 15, 2025
Job Description:
Seeking multiple Engineering (Coding) Subject Matter Experts to help design, run, and optimize data collection and evaluation workflows for GenAI research.
You’ll translate high-level research needs into scalable processes, produce and curate challenging domain problems, and ensure factual, bias-aware, high-quality datasets for LLM training.
- To Note: This is for an immediate project need. Project is approved for 3-months initially, with possibility to extend based on project/client demands.
Responsibilities:
- Partner with GenAI researchers/engineers to capture data needs and success criteria.
- Expand high-level requirements into clear, executable workflows for larger teams.
- Execute collection/evaluation workflows rapidly with minimal supervision.
- Innovate on workflows to maximize throughput and quality.
- Collaborate cross-functionally to maintain quality at scale.
- Conduct in-depth LLM-assisted research; gather reliable, up-to-date info.
- Craft original, high-quality content and hard problems for LLM eval/train.
- Perform rigorous fact-checking (precision/recall) to prevent misinformation.
Requirements:
- Education: Master’s with distinction or PhD in Engineering (Coding); top-tier institution preferred. Significant domain experience considered.
- Content development expertise across Engineering (Coding).
- Exceptional writing: clear, concise, engaging; across formats.
- Strong research & fact-checking; bias mitigation.
- Originality/creativity; distinct human voice.
- Detail orientation; precise data presentation; thorough proofreading.
- Communication: articulate complex info; strong collaboration.
- Understanding of AI/LLMs, their capabilities/limits.
- Prompt engineering and familiarity with AI writing tools.
- Ethical AI awareness and data literacy (collection, cleaning, transformation).
- Thrives in fast-paced, minimally supervised environments.
Originally posted on LinkedIn
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