Remote Senior AI/ML Quality Assurance Engineer

Trinnex Inc.; Toronto; Hybrid; CAD 144,000 - 253,000; Full time

Job summary

Trinnex Inc. is seeking a Senior AI/ML Quality Assurance Engineer to lead validation, testing, and monitoring of production AI/ML solutions.

You will ensure models are accurate, explainable, and compliant while partnering with Data Science, MLOps, Consulting, and Governance teams. The ideal candidate has strong Python/SQL/Git skills, experience with ML frameworks, and familiarity with Docker/Kubernetes and GCP.

Qualifications

• Experience validating, testing, or monitoring production machine learning models (classification, regression, or predictive analytics).
• Strong Python, SQL, and Git skills; comfortable handling spatial data structures.
• Experience with AI/ML testing, validation, and monitoring frameworks (pytest, MLflow, Deepchecks; Evidently AI, Arize).
• Familiarity with Docker, Kubernetes, and cloud environments (GCP).
• Ability to translate complex data science outputs into clear, actionable documentation.

Responsibilities

• Design, develop, and maintain automated testing frameworks for ML models and data pipelines.
• Validate various model types and ensure accuracy, reliability, and regulatory alignment.
• Perform model explainability and quality assessments for stakeholders.
• Collaborate with MLOps to monitor data drift and model degradation in production.
• Support root cause analysis, incident investigations, and recovery testing for AI/ML systems.
• Assist in evaluating Generative AI and RAG solutions and their safety controls.
• Develop validation reports and documentation to support responsible AI practices.
• Conduct quality reviews of AI deliverables before client release.

Skills

Python

SQL

Git

AI/ML testing

Docker

Kubernetes

GCP

Spatial data

Documentation

Cross-functional

Education

Bachelor's degree

Tools

GeoPandas

PostGIS

MLflow

pytest

Grafana

Datadog

Geo software

Job description

Trinnex Inc. is seeking a Senior AI/ML Quality Assurance Engineer to lead validation, testing, and monitoring of production AI/ML solutions.

You will ensure models are accurate, explainable, and compliant while partnering with Data Science, MLOps, Consulting, and Governance teams. The ideal candidate has strong Python/SQL/Git skills, experience with ML frameworks, and familiarity with Docker/Kubernetes and GCP.