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Flair Airlines

Machine Learning Engineer

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 18, 2026
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.

Benefits

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

Design, build, and deploy production-ready machine learning systems and end-to-end pipelines for classification, prediction, and optimization. Collaborate with cross-functional engineering teams to transform predictive models into scalable solutions that support business needs.

Requirements

Requires a Bachelor's or Master's degree in a technical field and at least three years of experience in machine learning or software engineering. Candidates must be proficient in Python, SQL, and cloud-based ML deployment with legal eligibility to work in Canada.

Skills

Python
SQL
Machine Learning
MLOps
PyTorch
TensorFlow
Scikit-learn
XGBoost
AWS
Docker
Git
CI/CD
API Development
Feature Engineering
Model Monitoring
Generative AI

Benefits

Medical Coverage
Dental Coverage
Disability Insurance
Life Insurance
Employee And Family Assistance Program
Pension Plan With Employer-Matched Contributions
Free And Discounted Flights

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
Data Science
Python
SQL
AWS
SageMaker
S3
Lambda
ECS
EKS
Glue
CloudWatch
MLflow
Airflow
Kubeflow
Docker
Git
CI/CD
LLM
RAG
Vector Databases
Embeddings
PyTorch
TensorFlow
XGBoost
Scikit-learn
MLOps
Aviation
Predictive Modeling
Anomaly Detection

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