Location
Remote
Salary
Not specified
Type
fulltime
Posted
Today
via linkedin
Job Description
STEM Jobs in Canada (Remote, Full-Time) — Engineering Roles on Rex.zone
Rex.zone connects engineers and technical professionals to remote, full-time roles supporting real-world AI/ML training workflows, including RLHF evaluation, data labeling, QA evaluation, prompt evaluation, named entity recognition, computer vision annotation, and content safety labeling.
What You Will Work On
- Create, validate, and improve training datasets used in LLM training pipelines
- Run RLHF-style preference judgments and structured LLM evaluations
- Perform QA evaluation and prompt evaluation; diagnose failure modes and improve model performance
- Support NLP tasks (e.g., named entity recognition) and CV tasks (e.g., bounding boxes/segmentation) as needed
- Apply content safety labeling and sensitive-content handling procedures
Key Responsibilities
- Follow detailed labeling/evaluation specs and document edge cases
- Review/adjudicate annotations, run spot checks, and track quality metrics
- Collaborate with engineering/research stakeholders to align evaluation rubrics with product goals
- Iterate on prompts, test sets, and guideline clarity to maintain reliable, auditable pipelines
Required Qualifications
- Mid-Senior experience in an engineering, STEM, or technical role
- Strong analytical reasoning, attention to detail, and guideline adherence
- Comfort with structured data, taxonomies, and evaluation rubrics
- Familiarity with NLP/ML concepts and data quality practices; ability to use Python for dataset review
Preferred
- Experience with RLHF evaluation, data labeling, QA evaluation, prompt evaluation, NER, CV annotation, or content safety labeling
- Exposure to gold sets, inter-annotator agreement, error analysis, dataset versioning, and evaluation-driven iteration
How To Apply
Create or update your Rex.zone profile, highlight relevant STEM experience, and apply with a short summary of your domain strengths (NLP, CV, content safety, or evaluation).
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