English (Canada) Language Specialist

About the role

This role evaluates English language capabilities in AI systems through structured testing and systematic analysis. The work documents model failures to improve reasoning and evaluation practices in a methodical manner. Results support training data quality for future AI applications in education and communication. You will analyze linguistic patterns and error traces to refine prompt engineering strategies. The role requires a strong understanding of how language models process and generate English text. Each evaluation run verifies factual accuracy and logical soundness using reproducible methods. You will contribute to strengthening future testing by identifying consistent failure modes. This position is critical for ensuring that AI systems handle English language tasks with higher reliability.

Key facts

What you'll do

Documented failure modes harden model reasoning and refine prompt engineering and evaluation metrics based on observed results and systematic testing. Each run with advanced models verifies factual accuracy and logical soundness and captures reproducible error traces for evaluation and future analysis. Observed model behavior and error patterns drive suggested improvements to evaluation metrics to strengthen future testing and data quality. You will perform structured evaluation of English language components to ensure consistent analysis across tasks. Common tools for language documentation and error tracking support the work and help maintain clarity in findings. Systematic model testing reveals edge cases that require adjustments in linguistic analysis approaches. You will interpret experiment outcomes to guide refinements in how models handle language complexity. Clear documentation benefits both model development and evaluation practices by providing traceable evidence.

Requirements

The posting states a pay range of $6 to $65 per hour for this contract position in Canada.

You must be a US citizen or a permanent resident to meet the visa requirements for this role.

Active Public Trust clearance is required to access sensitive materials and work on the project.

You must have the legal right to work in Canada under the applicable regulations for this engagement.

The role is classified as Entry Level within the Team structure and does not assume prior specialized experience.

You must be able to perform structured evaluation of English language components accurately and consistently.

Systematic model testing is a core responsibility and must be conducted with attention to detail.

You must be capable of documenting failure modes and translating observations into actionable suggestions.

Nice to have

Peer-reviewed publications, teaching experience, or hands-on linguistic analysis projects signal fit for this role and are viewed favorably during selection.

Practical notes

Company-sponsored benefits such as health insurance and paid time off do not apply to this contract position.

Typical interview steps

Data interviews commonly include a SQL or coding exercise, a statistics question, and a case study.

Candidates may be asked to design a metric, interpret an experiment, or build a small model as part of the assessment.

Some companies give a take-home analysis to complete before the final interview stage.

Expect questions about past projects and the business impact of your work during the interview process.

Interviewers often evaluate how you communicate uncertainty and business impact, not only the math behind the analysis.

Bringing a clean write-up of a past analysis to the interview is well received and can demonstrate your communication skills.

Good to know

High-quality training data determines how well language models support educational and research applications in real-world settings.

Linguistic expertise helps identify edge cases and reasoning gaps in AI systems during evaluation.

Clear documentation benefits both model development and evaluation practices by creating a reliable record of findings.

General knowledge of English language tools supports consistent analysis across tasks and improves efficiency.

This role emphasizes systematic testing and transparent reporting of model behavior to ensure accountability.

The work contributes to long-term improvements in how AI systems handle language-related tasks.

Questions to ask

Useful questions for the interview include what a typical week looks like for this role and how work is assigned on the team.

You may ask about what tools the team uses for language evaluation and error tracking in daily tasks.

It is reasonable to ask how feedback is provided and incorporated into future testing cycles.

Asking how the role has changed recently can reveal how the position is evolving within Meridial.

You may also ask what the team wishes it had known when joining to prepare for similar challenges.

Questions about the manager's priorities are especially valued and show engagement with the role.

Career growth

Data careers grow toward senior analyst, staff data scientist, or data engineering lead as skills and experience develop.

Many professionals specialize in machine learning, analytics, or infrastructure to deepen their expertise in specific areas.

Cross-functional work with product and engineering teams becomes more important at senior levels and expands your impact.

The field changes quickly, so continuous learning is part of the job and necessary for long-term success.

Professionals who can translate numbers into decisions tend to advance fastest in data-oriented roles.

Building a strong portfolio of past analyses matters more than degrees in many hiring decisions for this type of work.

You will refine communication skills by documenting processes and explaining findings to diverse stakeholders.

The role provides exposure to AI systems, evaluation methods, and data quality challenges in a structured environment.

Hour expectations for this contract role are defined in the engagement details provided during hiring discussions.

Travel is not expected as part of this role since it is conducted remotely from Canada.

No visa sponsorship is available for this position due to the specific citizenship or residency requirement.

Deadlines for deliverables will be set in collaboration with the team based on project timelines and evaluation needs.