Entry Level STEM Jobs United States (Remote, US)

Support AI/ML engineering-adjacent workflows that improve LLM training pipelines through high-quality data labeling, RLHF-style evaluation, QA evaluation, and prompt evaluation. You will apply annotation guidelines compliance and structured documentation to strengthen training data quality and model performance.

What You Will Do

• Execute data labeling across text, image, and multimodal datasets
• Perform QA evaluation using sampling plans, disagreement analysis, and error taxonomies
• Complete RLHF preference ranking and prompt evaluation aligned to rubrics
• Annotate NLP tasks (e.g., named entity recognition, intent classification) with consistent schemas
• Support computer vision annotation (bounding boxes, segmentation) as needed
• Apply content safety labeling policies for harmful or sensitive content
• Document edge cases and provide rationales to improve guidelines and training data quality
• Collaborate asynchronously with distributed engineering and ops partners
  
  

Required Qualifications

• US-based and available for remote, full-time work
• STEM background (degree, bootcamp, or equivalent experience) and quantitative reasoning
• Ability to learn and follow detailed annotation guidelines
• Strong written communication and attention to detail
• Familiarity with spreadsheets and basic Python or SQL for lightweight data checks
  
  

Preferred Qualifications

• Experience with LLM evaluation, RLHF, or prompt evaluation
• Exposure to NLP and/or computer vision annotation tools
• Understanding of content safety labeling and policy interpretation
• Experience with training data quality metrics or inter-annotator agreement
  
  

Compensation

Hourly base pay range: $30–$50/hr.

How To Apply

Apply via Rex.zone and highlight STEM projects, Python/SQL, and any experience with data labeling, QA evaluation, RLHF, prompt evaluation, or annotation guidelines compliance.