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STEM Research Engineer (Canada)

Rex.zone
United States
Full-time
3,000 – 5,000 / year
AI tools:
LLMs
Applications go directly to the hiring team

Full Description

STEM Research Jobs in Canada

Rex.zone is hiring a STEM Research Engineer to support applied AI/ML research and engineering workflows, including LLM training pipelines, dataset development, RLHF, prompt evaluation, and QA evaluation. This is a remote, full-time role focused on improving training data quality and measurable model performance across NLP and computer vision.

Key Responsibilities

* Design and execute applied STEM research experiments aligned to model performance improvement and deployment constraints

* Build and maintain LLM training pipelines combining data labeling, RLHF signals, and QA evaluation outputs

* Develop prompt evaluation protocols and scoring rubrics for large language model evaluation

* Implement training data quality checks: annotation guidelines compliance, inter-annotator agreement, and sampling audits

* Run error analysis for NLP and computer vision tasks (e.g., named entity recognition and annotation edge cases)

* Support content safety labeling workflows with taxonomies, adjudication rules, and escalation criteria

* Produce reproducible documentation, experiment logs, and code to ensure traceability

* Communicate findings and recommendations to technical and non-technical stakeholders

Required Qualifications

* Mid-Senior experience in STEM research, applied ML research, or engineering research roles

* Strong Python for data processing, experiment automation, and evaluation tooling

* Hands-on experience with NLP, computer vision, or multimodal evaluation

* Knowledge of data labeling, QA evaluation, and annotation guidelines compliance

* Familiarity with RLHF and prompt evaluation methods

* Strong experiment design and statistical reasoning

* Experience collaborating in remote, cross-functional teams

Compensation

$30–$50 per hour (base salary).

Remote, full-time.

Applications go to the hiring team directly