Jobs in Canada

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Added 1 month ago
QF
Senior Manager, Advanced Credit Risk Modelling (Questbank)
Questrade Financial Group
Toronto, ON · North York, ON
- Full-time
Work-life balance in a hybrid environment with at least 3 days in office
Added 1 month ago
Director, Data Science
Gore Mutual Insurance
Cambridge, ON · Toronto, ON
Added 1 month ago
Senior Manager, Advanced Credit Risk Modelling (Questbank)
Questrade Financial Group
Toronto, ON
Work-life balance in a hybrid environment with at least 3 days in office
Added 1 month ago
JI
Senior MLOps Developer | Développeur·euse MLOps senior
Jesta I.S.
Montreal, QC
- Full-time
Work Model: Hybrid; 2 days per week in the M
Added 1 month ago
C
Presales Solutions Architect
Centrilogic
Toronto, ON
- Full-time
Added 1 month ago
B
Enterprise Architect – AI and Data
BMO
Toronto, ON · FCP
- Full-time
Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch), cloud platforms (e.g., Azure, AWS, GCP), and MLOps tools.
Added 1 month ago
I
Sr. Machine Learning Engineer
Insight
Remote, Canada
- Full-time
- Remote
…integration into agent response loops, and operating the full MLOps lifecycle on Gemini Enterprise Agent Platform (GEAP). Along the way, you will get…
Added 1 month ago
CC
Product Owner, AI Factory
Cogeco Connexion
Montreal, QC
- Full-time
…Architecture Crew, this role drives the operational backbone (MLOps, LLMOps, AgentOps) that enables cross-functional business squads to repeatedly, safely, and cost-effectively build,…
Added 1 month ago
CC
Product Owner, AI Factory
Cogeco Connexion
Burlington, ON
- Full-time
…Architecture Crew, this role drives the operational backbone (MLOps, LLMOps, AgentOps) that enables cross-functional business squads to repeatedly, safely, and cost-effectively build,…
Added 1 month ago
C
Product Owner, AI Factory
Cogeco
Burlington, ON · Montreal, QC
- Full-time
…Architecture Crew, this role drives the operational backbone (MLOps, LLMOps, AgentOps) that enables cross-functional business squads to repeatedly, safely, and cost-effectively build,…
Added 2 months ago
AI and Data - Manager - AI/ML Engineer
EY
AB · Calgary, AB
To qualify for the role you must have
Added 1 month ago
ID
Data Scientist & Machine Learning Engineer
Identity Digital Inc.
Toronto, ON
- $87,000 to $114,000 CAD / year
- Full-time
…embeddings and vector databases, large language models, and modern MLOps / LLMOps…
Added 1 month ago
TC
Data AI Engineer
Tata Consultancy Services
Mississauga, ON
- $100,000 to $130,000 CAD / year
- Full-time
· MLOps & Deployment: Docker, Kubernetes/OpenShift, FastAPI
Added 1 month ago
E
Spécialiste IA et automatisation de processus
EXFO
Quebec, QC
- Full-time
Collaborer avec les développeurs MLOps à l’évolution de notre plateforme agentique en identifiant les besoins liés aux connecteurs, à l’orchestration, aux permissions et à l’intégration.
Added 1 month ago
TC
Lead Developer, Research & Development
The Citco Group Limited
Toronto, ON
- Full-time
The Lead Developer within the Transformation Office's R&D team will provide technical leadership for AI-enabled solutions supporting a strategic Fund Services transformation program using…
Added 1 month ago
C
AI Engineer
Cognizant
Toronto, ON
- Full-time
Implement DataOps and MLOps automation (CI/CD, data validation, model deployment, monitoring, drift detection)
Added 1 month ago
B
Sr Analyst, DevOps
Brookfield
Toronto, ON
- Full-time
The Senior AI Cloud Developer Analyst within Brookfield’s Technical Service Group (TSG) builds and delivers AI solutions from prototype to production, implementing scalable, secure and…
Added 1 month ago
A
Manager, Software Engineering
AltaML
Calgary, AB · Edmonton, AB · Toronto, ON
- Full-time
Familiarity with AI/ML solutions and modern MLOps or software delivery practices
Added 1 month ago
A
Manager, Software Engineering
AltaML
Calgary, AB
- Full-time
Familiarity with AI/ML solutions and modern MLOps or software delivery practices
Added 1 month ago
A
Manager, Software Engineering
AltaML
Edmonton, AB
- Full-time
Familiarity with AI/ML solutions and modern MLOps or software delivery practices
Added 1 month ago
NB
Generative AI Solutions Architect
National Bank of Canada
Montreal, QC
- Full-time
Contribute to the implementation of end-to-end solutions, including data pipelines, MLOps, system integrations, and monitoring/FinOps mechanisms.
Added 1 month ago
E
AI & Process Automation Specialist
EXFO
Quebec, QC · Greater Quebec City Metropolitan Area
- Full-time
Collaborer avec les développeurs MLOps à l’évolution de notre plateforme agentique en identifiant les besoins liés aux connecteurs, à l’orchestration, aux permissions et à l’intégration.
Added 1 month ago
BA
Sr Analyst, DevOps
Brookfield Asset Management
Toronto, ON · Brookfield Place
- Full-time
The Senior AI Cloud Developer Analyst within Brookfield’s Technical Service Group (TSG) builds and delivers AI solutions from prototype to production, implementing scalable, secure and…
Added 1 month ago
Staff Backend Engineer, Customer Value Optimization
HelloFresh
Toronto, ON
This means a minimum of 3 days in office per week
Added 1 month ago
TT
Senior HVAC Engineer
trane technologies
Montreal, QC
- Full-time
· Collaborate across AI research, MLOps, and algorithm teams to deliver production-ready solutions.

Insight

Sr. Machine Learning Engineer

Remote, Canada

Remote

Full-time

Apply on insight.eightfold.ai About employer

Applications open in a new tab.

Job details

Job type: Full-time
Workplace: Remote
Remote eligibility: Canada listed. Check the posting for province restrictions.
Posting language: English
Posted: Sep 16, 2026

Original job description

Requisition Number: 106424

Senior Machine Learning Engineer

Location:

You will have the flexibility to work fully remotely.

Insight at a Glance

14,000+ engaged teammates globally
$8.2 billion in revenue in 2025
Certified as a Great Place to work in 9 Countries in 2025
Fortune 500 Company (No. 447) in 2025
Received 25+ industry and partner awards in the past year
$1.4M+ total charitable contributions in 2024 by Insight globally

Now is the time to bring your expertise to Insight. We are not just a tech company; we are a people-first company. We believe that by unlocking the power of people and technology, we can accelerate transformation and achieve extraordinary results. As a Fortune 500 Solutions Integrator with deep expertise in cloud, data, AI, cybersecurity, and intelligent edge, we guide organizations through complex digital decisions.

About the role

As an Senior Machine Learning Engineer, you will lead the modeling work on enterprise engagements where ML models are often integrated directly into multi-agent systems. We will count on you to span data exploration, feature engineering, model development across multiple business segments, integration into agent response loops, and operating the full MLOps lifecycle on Gemini Enterprise Agent Platform (GEAP). Along the way, you will get to:

Build anomaly detection and regression models. Develop end-to-end pipelines that check data quality, engineer features, train, tune and evaluate models, and perform either batch or online inference.
Migrate legacy ML workloads onto GEAP (formerly known as Vertex AI). Translate existing models from platforms such as Dataiku or SageMaker into KFP-based pipeline templates on GEAP.
Own drift detection and retraining. Implement input and output distribution shift detection and accuracy regression checks. Define per-model thresholds and retraining cadence, set up alerting and logic for decisions on when to re-train a model. Ensure retraining deploys through the standard CD pipeline with canary, approval gate, and automated rollback.
Register everything. Ensure every model is registered in GEAP Model Registry with model cards capturing ownership, lineage, evaluation results, and lifecycle state.
Be AmbITious: This opportunity is not just about what you do today but also about where you can go tomorrow. When you bring your hunger, heart, and harmony to Insight, your potential will be met with continuous opportunities to upskill, earn promotions, and elevate your career.

What we’re looking for

5+ years applied ML engineering, with at least 2 years productionizing models at scale. You have shipped models that real users or downstream systems depend on, not just notebooks.
Deep GEAP experience. Model Registry, Pipelines (KFP), Experiments, Feature Store, and Workbench. You can stand a project up from zero, not just consume an existing one.
Strong regression and anomaly detection chops. Gradient boosting (XGBoost / LightGBM / CatBoost), classical statistical anomaly methods (IQR, isolation forests, robust z-scores), and at least one deep approach (autoencoders, normalizing flows). You can defend an architecture choice with empirical results, not preferences.
Production Python. Type-annotated, tested, packaged. Comfortable with pandas, NumPy, scikit-learn, and the GEAP SDK. Familiar with KFP DSL for pipeline authoring.

The base salary range for this position is typically $140,000 CAD to $160,000 CAD with additional bonus and benefits available. However, compensation decisions are dependent on the facts and circumstances of each case, including experience and location, and we will also consider candidates outside of this range as necessary.

What you can expect
We’re legendary for taking care of you, your family and to help you engage with your local community.

But what really sets us apart are our core values of Hunger, Heart, and Harmony, which guide everything we do, from building relationships with teammates, partners, and clients to making a positive impact in our communities.

Join us today, your ambITious journey starts here.

Insight is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, sexual orientation or any other characteristic protected by law.

When you apply, please tell us the pronouns you use and any reasonable adjustments you may need during the interview process.

At Insight, we celebrate diversity of skills and experience so even if you don’t feel like your skills are a perfect match - we still want to hear from you!

Insight does not accept unsolicited resumes from recruiters or employment agencies. Unsolicited resumes will be treated as direct applications from the candidate, and recruiters or agencies who submit candidates for this position without a prior, written vendor agreement will not be eligible for any form of compensation, even if the candidate is hired.

Posting Notes: Any City/Province in Canada || Alberta (CA-AB) || Canada (CA) || Data & AI || None || CA - Calgary, AB ||

Apply on insight.eightfold.ai About employer

More about this job

Responsibilities

The Senior Machine Learning Engineer will lead modeling work for enterprise engagements, integrating ML models into multi-agent systems. Responsibilities include building end-to-end pipelines, managing the MLOps lifecycle on the GEAP platform, and performing model retraining and drift detection.

Requirements

Candidates must have 5+ years of applied ML engineering experience, including at least 2 years of productionizing models at scale. Proficiency in Python, GEAP, and various machine learning frameworks like XGBoost and Scikit-learn is required.

Skills

Machine Learning
MLOps
Python
GEAP
Vertex AI
KFP
Anomaly detection
Regression
Data engineering
Feature engineering
XGBoost
LightGBM
CatBoost
Pandas
NumPy
Scikit-learn

Benefits

Bonus
Remote work flexibility

Remote locations

Canada

Remote locations (standardized)

Canada

Visa sponsorship

Not detected in the job text

Keywords

Machine Learning
MLOps
Python
GEAP
Vertex AI
KFP
Anomaly detection
Regression
Data engineering
Feature engineering
XGBoost
LightGBM
CatBoost
Pandas
NumPy
Scikit-learn
Cloud
Data
AI
Cybersecurity
Intelligent edge
Model registry
Batch inference
Online inference
Drift detection
CD pipeline
Canary deployment
Dataiku
SageMaker
Autoencoders

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Work requirements

Jobs in Canada