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STEM Jobs in Canada — Remote Full-Time Engineer

Rex.zone

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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