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Added 2 hours ago
AI Architect, Manager
Avanade
Toronto, ON
Full-time
Added 11 hours ago
Senior Machine Learning Engineer Specialist – AI Centre of Excellence (35668)
Myticas Consulting
Canada
Contract
Primary Focus: Machine Learning Engineering, MLOps & Production AI Solutions
Added 11 hours ago
AI Platform Engineer (35577)
Myticas Consulting
Toronto, ON
Contract
Implement CI/CD pipelines, Infrastructure-as-Code, and MLOps/LLMOps best practices.
Added 11 hours ago
AI Engineer (35578)
Myticas Consulting
Toronto, ON
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Implement MLOps, LLMOps, CI/CD, and cloud deployment best practices.
Added 2 days ago
Apps Dev Tech Sr Lead Analyst
Citi
Mississauga, ON
Full-time
Added 7 days ago
Data Scientist
MLSE (Maple Leaf Sports & Entertainment Partnership)
Toronto, ON · Scotiabank Arena
Full-time
Familiarity with modern MLOps workflows, containerization (Docker), and cloud infrastructure (AWS or GCP) for scaling predictive models.
Added 3 days ago
AI Lead Architect, Software and Platforms Architecture (T & I) (Telework/Hybrid)
CBC/Radio-Canada
Ottawa, ON · Toronto, ON · Montreal, QC
Full-time
Added 3 days ago
Lead, Machine Learning Engineer, GFT
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Toronto, ON
Full-time
Experience with MLOps practices, model serving, monitoring, and CI/CD pipelines for ML systems
Added 2 days ago
Sr. Data Scientist
Charger Logistics Inc
Brampton, ON
Full-time
Operate MLOps workflows on Google Cloud using Vertex AI Pipelines, Feature Store, and Model Registry, supporting model training, deployment, monitoring, and drift detection.
Added 1 month ago
AI Lead Architect, Software and Platforms Architecture (T & I) (Telework/Hybrid)
Radio-Canada
Montreal, QC
Full-time
Added 1 month ago
AI Lead Architect, Software and Platforms Architecture (T & I) (Telework/Hybrid)
CBC/Radio-Canada
Montreal, QC
Full-time
Added 2 days ago
Engineering Manager, Forward Deployed Engineering (LLM)
Baseten
Toronto, ON
$260,000 to $380,000 USD / year
Full-time
…applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing…
Added 2 days ago
Applied AI Engineer
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Mississauga, ON
Full-time
Engineer for production across the full SDLC (build → test → deploy → monitor → iterate). Implement MLOps/GenAIOps practices (CI/CD, reproducibility, environment parity, model/prompt/agent…
Added 2 days ago
AI Platform Engineer with DevOps
Apptoza Inc.
Halifax, NS
Contract
· Champion developer-experience and best practices in conjunction with DevOps to ensure no developer is left behind
Added 2 days ago
Machine Learning Engineer
Flair Airlines Ltd.
Toronto, ON · Vancouver, BC · Edmonton, AB · Calgary, AB
Full-time
Implement MLOps practices, including experiment tracking, model versioning, CI/CD, automated retraining, and model monitoring.
Added 2 days ago
Data Engineer II (Restaurant AI CoPilot)
OpenTable
Toronto, ON
Knowledge or experience in Machine Learning development (e.g., NLP, LLMs, RAG, recommendations, or MLOps).
Added 2 days ago
Sr. Data Scientist
Charger Logistics Inc.
Brampton, ON
Full-time
Operate MLOps workflows on Google Cloud using Vertex AI Pipelines, Feature Store, and Model Registry, supporting model training, deployment, monitoring, and drift detection.
Added 3 days ago
Machine Learning Engineer
Flair Airlines
Toronto, ON
Full-time
Implement MLOps practices, including experiment tracking, model versioning, CI/CD, automated retraining, and model monitoring.
Added 3 days ago
2027 Graduate Program, Technology Services - Product and Initiative Management
Bell
Montreal, QC · Verdun, QC
Build, test, and scale production-grade ML and Generative AI applications using MLOps best practices (CI/CD, monitoring, and automation).
Added 3 days ago
2027 Graduate Program, Technology Services - Emerging AI and Data Solutions
Bell
Montreal, QC · Verdun, QC
Build, test, and scale production-grade ML and Generative AI applications using MLOps best practices (CI/CD, monitoring, and automation).
Added 3 days ago
Senior Director, Applied AI and Quantum Research
CIBC
Toronto, ON
Full-time
…partnerships across lines of business, technology, architecture, MLOps, and governance teams. In this role, you'll champion the translation of research into scalable, production-ready…
Added 2 days ago
AI Platform Engineer with DevOps Experience
Zodiac Solutions, Inc
Halifax, NS
Full-time
We are looking for a Developer obsessed with efficiency and automation to be part of an autonomous team to deliver services for application teams across Capital Markets. An open minded…
Added 10 days ago
AI Pre-Sales Consultant
Thinkpivot
Toronto, ON
Full-time
MLOps: Familiarity with MLflow, Kubeflow, or Weights & Biases for model lifecycle management.
Added 3 days ago
Responsable - Plateforme IA (Lead AI Platform Engineer)
CGI
Montreal, QC
Full-time
Practical DevOps/MLOps knowledge, including CI/CD, containers such as Docker, and basic observability.
Added 3 days ago
Delivery Lead - Data & AI
Raise
Mississauga, ON
Full-time
…semantic modelling, Power BI, analytics, ML model lifecycles, MLOps, APIs, CI/CD, data quality and production…

Flair Airlines Ltd.

Machine Learning Engineer

Toronto, ON, Canada
Vancouver, BC, Canada
Edmonton, AB, Canada
Calgary, AB, Canada

Job type: Full-time
Posting language: English
Posted: Sep 18, 2026

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Original job description

Take Your Career to New Heights with Flair Airlines

We’re here to make air travel affordable for everyone, and we’re looking for talented individuals who want to help us continue changing the industry for the better. As Canada’s most reliable airline, we're all about offering real value. As we continue to expand our network, increase flight frequencies, and introduce more services, we’re looking for passionate team members to help us in our mission to make air travel accessible for everyone. We know who we are, and we’re confident in our approach.

Your Team:

Join the Digital - Engineering team at Flair as a Machine Learning Engineer, where you will play a key role in designing, building, deploying, and maintaining production machine learning systems. Reporting to the Director, Engineering, you will work closely with Data Engineers, Software Engineers, and business stakeholders to transform data and predictive models into reliable, scalable solutions that support business needs. This is a hands-on role focused on developing production-ready machine learning solutions, improving model performance and reliability, and ensuring machine learning systems operate effectively at scale. You will also have the opportunity to contribute to the ongoing development and evolution of Flair’s technology platform.

This is a full-time, on-site position that can be based at any of our Edmonton (YEG), Calgary (YYC), Vancouver (YVR), or Toronto (YYZ) offices.

A Day in the Life:

As a Machine Learning Engineer, you will:

Design, develop, and deploy machine learning models for classification, prediction, recommendation, anomaly detection, forecasting, and optimization.
Build end-to-end machine learning pipelines, including data preparation, feature engineering, model training, evaluation, deployment, and monitoring.
Develop production-quality Python code using machine learning frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow.
Deploy machine learning models as APIs, batch-processing jobs, or real-time inference services.
Build and maintain cloud-based machine learning infrastructure using platforms such as AWS, Azure, or GCP.
Work with large datasets using SQL, data warehouses, and distributed processing frameworks.
Implement MLOps practices, including experiment tracking, model versioning, CI/CD, automated retraining, and model monitoring.
Monitor model performance, data quality, model drift, latency, and reliability in production environments.
Collaborate with DevOps Engineers to productionize experimental models and transform prototypes into reliable, scalable systems.
Partner with Data Engineers to develop reliable datasets and pipelines for model training and inference.
Evaluate emerging machine learning and generative AI technologies, including large language models (LLMs), embeddings, vector databases, and retrieval-augmented generation (RAG), where appropriate.
Communicate model performance, limitations, and business impact clearly to both technical and non-technical stakeholders.
Perform additional duties as required to support business objectives.

What You Bring to the Role:

The preferred candidate should exemplify Flair's core values of respect, honesty, accountability, and efficiency while demonstrating success in previous roles. Additionally, we are seeking individuals who possess:

Education:
- Bachelor’s or master’s degree in computer science, Data Science, Statistics, Engineering, or a related field
Experience:
- Minimum of three (3) years of experience in machine learning, data science, software engineering, or a related technical field, with hands-on experience developing and deploying machine learning solutions.
- Experience developing machine learning solutions using libraries such as scikit-learn, XGBoost, PyTorch, or TensorFlow.
- Experience deploying applications or machine learning models in a cloud environment.
- Experience working with SQL and large datasets.
- Experience with Docker, Git, CI/CD, APIs, and software engineering practices.
- Experience with AWS services such as SageMaker, S3, Lambda, ECS/EKS, Glue, and CloudWatch is an asset.
- Familiarity with MLOps tools such as MLflow, SageMaker Pipelines, Airflow, Kubeflow, or similar platforms is an asset.
Skills and Abilities:
- Strong programming skills in Python.
- Strong knowledge of SQL and data processing.
- Strong understanding of core machine learning concepts, including supervised and unsupervised learning, feature engineering, model evaluation, overfitting, cross-validation, and hyperparameter tuning.
- Strong analytical and problem-solving skills.
- Ability to develop reliable, production-quality machine learning solutions.
- Ability to work collaboratively with Data Engineers, Software Engineers, DevOps Engineers, and other technical teams.
- Ability to communicate technical concepts and model outcomes clearly to technical and non-technical stakeholders.
Requirements:
- Clear criminal record check and satisfactory references.
- Must be legally eligible to work in Canada without restriction.

Why You’ll Love Working Here:

At Flair, we prioritize our teams by cultivating a supportive, collaborative work environment filled with opportunities for growth. Investing in our people is at the heart of what we do because your success fuels our collective achievements. We are dedicated to fostering a workplace where leaders thrive, innovation flourishes, and every team member feels valued and empowered.

From the moment you join us, you’ll have access to a comprehensive benefits package designed to support your well-being - because when you’re at your best, so are we. This benefits package includes:

Comprehensive Salary - A salary that reflects your experience and contributions.
Comprehensive Benefits - Competitive medical and dental coverage, disability insurance, life insurance, and an employee and family assistance program.
Retirement Savings – A pension plan with employer-matched contributions.
Unlimited Travel Perks – Enjoy free and discounted flights for you and your travel companions.

If you’re ready to join a team that’s bold, innovative, and fun, we want to hear from you!

Your Career, Your Journey - Join Flair!

If you’re ready to embark on this exciting journey with Flair Airlines, please submit your resume through the job posting and answer a few questions about your experience and suitability for the role. We look forward to your application.

Apply by: When a successful candidate is identified.

At Flair, we’re committed to building an inclusive, equal, and accessible workplace that welcomes diverse talent. We encourage candidates from all backgrounds to apply. If you need accommodation during the selection process, just let us know.

We thank all applicants for their interest in Flair; however, only those selected to continue in the process will be contacted.

Website: flyflair.com

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More about this job

Responsibilities

You will design, develop, and deploy production-ready machine learning models and pipelines to support business needs. Additionally, you will collaborate with cross-functional engineering teams to maintain scalable infrastructure and monitor model performance in production.

Requirements

Candidates must hold a bachelor's or master's degree in a technical field and possess at least three years of hands-on experience in machine learning or software engineering. Proficiency in Python, SQL, and cloud-based machine learning frameworks is required, along with legal eligibility to work in Canada.

Skills

Python
Machine learning
SQL
Cloud computing
AWS
MLOps
Data engineering
Scikit-learn
XGBoost
PyTorch
TensorFlow
Docker
Git
CI/CD
Predictive modeling
Data analysis

Benefits

Medical coverage
Dental coverage
Disability insurance
Life insurance
Employee and family assistance program
Pension plan
Free and discounted flights

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning Engineer
Python
AWS
SQL
MLOps
Scikit-learn
XGBoost
PyTorch
TensorFlow
Docker
Git
CI/CD
SageMaker
Data Engineering
Predictive Modeling
Anomaly Detection
Generative AI
LLMs
Vector Databases
RAG
Cloud Infrastructure
Distributed Processing
Model Monitoring
Feature Engineering
Data Warehousing
API Development
Software Engineering
Statistics
Computer Science
Data Science

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