ML Engineer

CreatorIQ

Machine Learning Engineer developing applied ML solutions as part of Product Innovations team at CreatorIQ. Partnering with Data Science and Engineering to deploy reliable ML systems at scale.

Posted 7/18/2026full-timeToronto • 🇨🇦 CanadaMid-LevelSenior💰 CA$150,000 - CA$188,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in deploying and monitoring ML systems in production, with a strong foundation in Python and the modern data/ML stack. Proficient in evaluation methodologies for ML systems and effective collaboration with data scientists and engineers.

Highest-signal resume keywords

ML Systems DeploymentPython ProgrammingCloud Experience (AWS or GCP)Evaluation Methodologies (Golden Datasets, IAA)NLP or ML Systems Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning EngineeringModel MonitoringVector EmbeddingsNLP ClassificationRegression TestingDrift DetectionVersioningPrecision/Recall EvaluationGround-Truth PipelinesModel-as-a-Judge Frameworks

Soft Skills

Collaborative Communication

Industry Keywords

MLOpsInter-Annotator AgreementSimilarity PatternsData Annotation WorkflowsPII Scrubbing

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Deploy and monitor ML systems in production.
Own the evaluation stack - golden datasets, "model-as-a-judge" frameworks, inter-annotator agreement, and regression tests that gate releases.
Build and maintain our vector embeddings ecosystem and the retrieval, classification, and similarity patterns that sit on top of it.
Partner with Data Science on annotation workflows, PII scrubbing, and ground-truth pipelines.
Improve our MLOps foundations - versioning, observability, drift detection.
Translate fuzzy product problems into measurable AI features with clear success criteria.

Requirements

What you’ll need

4–7 years of professional software or ML engineering experience, including 2+ years shipping ML systems to production.
Strong Python; comfort with the modern data/ML stack.
Hands-on experience deploying and monitoring models in at least one major cloud (AWS or GCP); willingness to learn the other.
Production experience with NLP or ML systems - classification, NER, embeddings, ranking, similarity, or LLM-powered features.
Practical experience with evaluation for ML or LLM systems - golden datasets, model-as-a-judge, IAA, precision/recall, or equivalent.
Collaborative communicator - you work well alongside data scientists and engineers, and can clearly explain ideas, requirements, and tradeoffs to non-technical stakeholders.

Benefits

Comp & perks

Work/life harmony: vacation, floating and set holidays, wellness allowance, and paid parental leave.
Whole Health Package: medical, dental, vision, life, disability insurance, and more.
Surprise meal stipends: work from home can’t stop the enjoyment of someone else making a meal for you!
Guidance: utilize our learning platform to fully get the training and tools you’ll need to become successful here from your first day with us.
People: work with talented, collaborative, and friendly people who love what they do.