Rex Usa

About The Role

Remote STEM Jobs in India at Rex.zone focus on applied engineering work that supports AI/ML training pipelines, including data labeling, RLHF evaluation, prompt evaluation, and QA evaluation for large language models. You will collaborate with globally distributed teams to produce high-quality training data and improve model performance across NLP, computer vision, and content safety labeling workflows.

Key Responsibilities

Design and execute annotation and evaluation workflows for NLP, computer vision, and multimodal tasks Implement RLHF and prompt evaluation protocols using well-defined rubrics and calibration Define and enforce annotation guidelines compliance; maintain edge‐case documentation Run QA evaluation audits, spot checks, inter‐annotator agreement analysis, and error taxonomy tracking Curate datasets for named entity recognition, classification, ranking, summarization, and safety policy adherence Use Python and data tooling to automate checks, sampling plans, reporting, and quality metrics Required Qualifications Mid‐senior STEM/engineering background (CS, EE, math, physics, statistics, or related) Strong Python skills; comfort with structured and unstructured data Practical understanding of LLM evaluation, data labeling, and QA evaluation concepts Experience with NLP tasks (e.g., NER, text classification, relevance ranking, summarization) Ability to interpret guidelines, resolve ambiguity, and communicate asynchronously in a remote setting Preferred Qualifications Experience with RLHF pipelines, preference ranking, or rubric‐based evaluation Familiarity with computer vision annotation (bounding boxes, polygons, segmentation) Experience building quality systems (sampling, audits, calibration sessions, disagreement resolution) Exposure to content safety labeling or trust & safety workflows Compensation Competitive hourly base pay: $30–$50 per hour How To Apply Visit Rex.zone and search for "Remote STEM Jobs in India" to find matching roles and apply. Highlight STEM engineering impact, Python/data tooling, and experience with data labeling, RLHF, LLM evaluation, training data quality, and annotation guidelines compliance.