20 meilleures offres (mlops engineer, toronto, on) (à pourvoir)

AI Engineer Intelligent Systems & Analytics
QMC Metering Solutions —North York, ON
- Temps plein
- Travail hybride
- Azure
- Informatique
- DevOps
- Programmes de Bien-être
- Aide au Transport Quotidien
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il y a 12 jours
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BDO —Toronto, ON
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Deloitte —Toronto, ON
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Recutify Inc. —Toronto, ON
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BDO —Toronto, ON
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Lucrodyne —Toronto, ON
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Je souhaite recevoir la dernière alerte emploi pour les postes de ce type : mlops engineer (toronto, on)

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AI Engineer Intelligent Systems & Analytics

QMC Metering Solutions -
North York, ON

Postuler rapidement

Détails du poste

Permanent | Temps plein

Profil recherché

TensorFlow
Azure
Droit
Informatique
Internet des objets
PyTorch
DevOps
Ingénierie
Mathématiques
Bases de données
Analyse statistique
AWS
Esprit d'analyse
Docker
Apprentissage automatique
Intelligence artificielle
Évaluation de modèle
Python
Science des données

Description complète du poste

AI Engineer - Intelligent Systems & Analytics

QMC Metering Solutions supplies and integrates several meter technologies to effectively monitor the consumption of electricity, water, gas and thermal energy consumption of commercial and residential properties. We have offices in Port Coquitlam, Ottawa and Toronto and have a support and distribution network across the country including Edmonton and Montreal.

QMC is seeking an experienced AI Engineer to design and implement machine learning and AI-driven capabilities across our cloud-based utility data and IoT platforms.

This role focuses on transforming large-scale time-series and sensor datasets into predictive insights, automation tools, and intelligent workflows. The ideal candidate has experience deploying ML systems in production environments and building scalable AI services in cloud-native architectures. You will work closely with backend engineers, product teams, and field technology specialists to develop intelligent systems that improve operational efficiency, data quality, and system performance.

Key Responsibilities

Machine Learning & Predictive Modeling

Design, develop, and deploy machine learning models for anomaly detection, forecasting, and predictive maintenance.
Work with large-scale time-series datasets from metering and IoT systems.
Perform feature engineering and model optimization.
Run experiments, validate results, and measure model accuracy.
Retrain and tune models to prevent drift and maintain performance.

AI Application Development

Build AI-powered features within SaaS applications.
Develop natural language interfaces and intelligent query tools.
Implement Retrieval-Augmented Generation (RAG) pipelines where appropriate.
Design AI assistants to support operational workflows and technical users.
Ensure outputs respect security, data privacy, and role-based permissions.

Data & Infrastructure

Develop scalable data pipelines for ML model training and inference.
Implement CI/CD processes for model deployment.
Contribute to cloud architecture design (AWS and/or Azure).
Monitor model performance and maintain production reliability.
Collaborate on infrastructure automation and DevOps practices.

Edge & IoT Intelligence (Preferred)

Develop lightweight analytics for device-level or near-edge processing.
Optimize models for performance in constrained environments.
Support telemetry analysis and automated device health monitoring.

Required Qualifications

5+ years of experience in machine learning engineering or applied data science.
Degree in Computer Science, Engineering, Mathematics, or related discipline.
Strong Python experience (TensorFlow, PyTorch, Scikit-learn, or similar).
Experience deploying ML models in production systems.
Demonstrated experience in 'Copilot Studio and associated AI Apps'
Experience working with time-series or sensor-based data.
Solid understanding of statistical analysis and experimental design.

Technical Skills

Machine Learning

Time-series forecasting
Anomaly detection
Model evaluation frameworks
Feature engineering
Model versioning and lifecycle management

Cloud & DevOps

AWS and/or Azure
Docker and containerized deployments
CI/CD pipelines
Infrastructure automation

Data Systems

ETL pipeline design
Large dataset processing
Experience with modern databases or data warehouses

Preferred Experience

Experience with IoT or industrial data environments.
Familiarity with LLM deployment and prompt engineering.
Experience building secure, multi-tenant AI systems.
Knowledge of MLOps best practices.

Core Competencies

Strong analytical and problem-solving skills.
Ability to work independently on complex, non-routine challenges.
Clear technical communication.
Collaborative mindset across cross-functional teams.
Research-oriented and continuously learning.

What Success Looks Like

ML models successfully deployed into production environments.
Measurable improvements in operational insight and automation.
Stable and scalable AI services integrated into SaaS platforms.
Clear model performance metrics and monitoring in place.

Why work with us?

QMC is a leading North American provider of innovative sub‑metering solutions, powered by a diverse and inclusive team. . We offer a supportive, growth‑focused workplace with:

Diverse, inclusive, people‑focused culture
Active DEIB and Sustainability committees
Hybrid work options (role‑dependent)
Competitive benefits plan + bonus incentives
100% tuition reimbursement
Annual wellness reimbursement
Company‑matched RSP contributions
Paid volunteer day
Transit subsidy
Strong recognition programs
Company social events + team‑building activities

Join us and grow your career with a team that values your impact!

Job Types: Full-time, Permanent

Benefits:

Commuter benefits
Company events
Dental care
Employee assistance program
Extended health care
Life insurance
On-site parking
Paid time off
RRSP match
Tuition reimbursement
Vision care
Wellness program
Work from home

Experience:

machine learning engineering or applied data science: 5 years (required)
strong Python : 5 years (required)

Work Location: Hybrid remote in North York, ON M3C 1Z3

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Je souhaite recevoir la dernière alerte emploi pour les postes de ce type : mlops engineer (toronto, on)

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