Online STEM Engineer (Canada)

Rex.zone; United States; On-site; USD 80,000 - 110,000; Full time

Job summary

Rex.zone is hiring an Online STEM Engineer (Remote, USA) to enhance AI/ML training pipelines through tasks such as data labeling, QA evaluation, and model performance documentation. This full-time position calls for mid-senior professionals with strong Python skills, experience in QA evaluation, and familiarity with machine learning concepts. The role focuses on improving training data quality and achieving measurable outcomes in training data performance. Interested candidates should submit a resume with relevant experience and documentation samples.

Qualifications

• Mid-Senior experience delivering production or applied research engineering work.
• Comfortable with data processing, evaluation harnesses, and reproducible experiments.
• Experience enforcing annotation guidelines compliance.

Responsibilities

• Own end-to-end remote engineering tasks supporting AI/ML data and evaluation workflows.
• Build and maintain annotation tooling and lightweight pipelines.
• Execute QA evaluation and ensure annotation guidelines compliance.
• Run prompt evaluation and detect regressions, bias, and failure modes.
• Partner with stakeholders to define metrics and documentation for improvement.

Skills

Strong Python skills

Familiarity with machine learning concepts

Experience in QA evaluation

Ability to communicate clearly in remote teams

Job description

Online STEM Jobs Canada — Remote Engineering Rex.zone is hiring an Online STEM Engineer (Canada) to support AI/ML training pipelines through RLHF evaluation, data labeling, QA evaluation, and prompt/LLM evaluation. This is a full-time, fully remote role focused on improving training data quality and measurable model performance outcomes.

What You Will Do

• Own end-to-end remote engineering tasks supporting AI/ML data and evaluation workflows, including RLHF scoring and rubric design
• Build and maintain annotation tooling and lightweight pipelines to increase throughput and training data quality
• Execute QA evaluation, audit sampling, and inter-annotator agreement checks to ensure annotation guidelines compliance
• Run prompt evaluation and large language model evaluation to detect regressions, bias, and failure modes
• Partner with stakeholders to define metrics, acceptance criteria, and documentation for model performance improvement

Core Workstreams

• NLP: named entity recognition, text classification, instruction-following evaluation, response ranking
• Computer Vision: bounding boxes, polygons, keypoints, and CV annotation QA
• Content Safety: policy-aligned labeling, edge-case taxonomy building, escalation workflows

Required Qualifications

• Mid-Senior experience delivering production or applied research engineering work
• Strong Python skills; comfortable with data processing, evaluation harnesses, and reproducible experiments
• Familiarity with machine learning concepts, LLM evaluation, and data labeling at scale
• Experience enforcing annotation guidelines compliance and performing QA evaluation
• Clear communication in distributed, remote-first teams

How To Apply

Submit your application with a resume and a short summary of relevant NLP, computer vision annotation, RLHF, data labeling, or QA evaluation experience. Include examples of documentation you have written (rubrics, guidelines, evaluation plans) and reproducible work samples where applicable.