AI Research Jobs in Canada (Remote, Full-Time)

Rex.zone; United States; Remote; USD 41,328 - 68,880; Part time

Job summary

A tech company is seeking an AI Researcher to support end-to-end research for modern AI systems. This remote role involves designing experiments, defining evaluation protocols, and improving evaluation rigor for large language models. Key responsibilities include developing AI research experiments, performing error analysis, and supporting data quality practices. Ideal candidates will have a fundamental understanding of AI and machine learning, along with experience in NLP or computer vision. Competitive pay ranges from $30 to $50 per hour.

Qualifications

• Experience with hands-on RLHF concepts including preference data and reward modeling.
• Familiarity with training data quality practices.
• Ability to collaborate cross-functionally with engineering teams.

Responsibilities

• Develop and run AI research experiments.
• Design evaluation harnesses for model evaluation.
• Define RLHF and preference modeling evaluation protocols.
• Perform error analysis and prompt evaluation.
• Build reproducible pipelines for data curation.

Skills

AI research fundamentals

Machine learning research fundamentals

Experience with large language models

Strong experiment design

Statistics basics

NLP knowledge

Computer vision knowledge

Job description

About The Role

This Remote, FULL_TIME AI Research position supports end-to-end research and applied experimentation for modern AI systems, including LLM training pipelines, RLHF evaluation, prompt evaluation, and model performance improvement. You will design experiments, define evaluation protocols, and improve evaluation rigor through robust measurement, dataset strategy, and QA evaluation workflows.

Key Responsibilities

• Develop and run AI research experiments across NLP, computer vision, and multimodal settings
• Design evaluation harnesses for large language model evaluation, including offline/online metrics
• Define RLHF and preference modeling evaluation protocols (rubrics, sampling plans, inter-rater reliability)
• Partner with data labeling teams to improve training data quality and annotation guidelines compliance
• Perform error analysis, ablation studies, and prompt evaluation to identify failure modes
• Build reproducible pipelines for dataset curation, data labeling audits, and QA evaluation
• Translate research findings into engineering-ready requirements and measurable acceptance criteria
• Support content safety labeling strategy and risk analysis for model outputs

Requirements

• AI research and machine learning research fundamentals
• Experience with large language models and model evaluation
• Hands‑on RLHF concepts (preference data, reward modeling, evaluation)
• Strong experiment design and statistics basics
• Familiarity with training data quality practices and dataset documentation
• NLP and/or computer vision domain knowledge
• Ability to collaborate cross‑functionally with engineering and data operations

Compensation

$30–$50 per hour (HOURLY)

How To Apply

Apply via Rex.zone with a resume and relevant research artifacts (papers, technical reports, repositories, or evaluation write-ups) demonstrating model performance improvement.